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e.content?e.content:e.content.map(s).join(""):""};e.hooks.add("after-tokenize",(function(e){"jsx"!==e.language&&"tsx"!==e.language||i(e.tokens)}))}(C),function(e){var t=e.util.clone(e.languages.typescript);(t=(e.languages.tsx=e.languages.extend("jsx",t),delete e.languages.tsx.parameter,delete 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e.languages.kotlin["class-name"];var t={"interpolation-punctuation":{pattern:/^\$\{?|\}$/,alias:"punctuation"},expression:{pattern:/[\s\S]+/,inside:e.languages.kotlin}};e.languages.insertBefore("kotlin","string",{"string-literal":[{pattern:/"""(?:[^$]|\$(?:(?!\{)|\{[^{}]*\}))*?"""/,alias:"multiline",inside:{interpolation:{pattern:/\$(?:[a-z_]\w*|\{[^{}]*\})/i,inside:t},string:/[\s\S]+/}},{pattern:/"(?:[^"\\\r\n$]|\\.|\$(?:(?!\{)|\{[^{}]*\}))*"/,alias:"singleline",inside:{interpolation:{pattern:/((?:^|[^\\])(?:\\{2})*)\$(?:[a-z_]\w*|\{[^{}]*\})/i,lookbehind:!0,inside:t},string:/[\s\S]+/}}],char:{pattern:/'(?:[^'\\\r\n]|\\(?:.|u[a-fA-F0-9]{0,4}))'/,greedy:!0}}),delete e.languages.kotlin.string,e.languages.insertBefore("kotlin","keyword",{annotation:{pattern:/\B@(?:\w+:)?(?:[A-Z]\w*|\[[^\]]+\])/,alias:"builtin"}}),e.languages.insertBefore("kotlin","function",{label:{pattern:/\b\w+@|@\w+\b/,alias:"symbol"}}),e.languages.kt=e.languages.kotlin,e.languages.kts=e.languages.kotlin}(C),C.languages.c=C.languages.extend("clike",{comment:{pattern:/\/\/(?:[^\r\n\\]|\\(?:\r\n?|\n|(?![\r\n])))*|\/\*[\s\S]*?(?:\*\/|$)/,greedy:!0},string:{pattern:/"(?:\\(?:\r\n|[\s\S])|[^"\\\r\n])*"/,greedy:!0},"class-name":{pattern:/(\b(?:enum|struct)\s+(?:__attribute__\s*\(\([\s\S]*?\)\)\s*)?)\w+|\b[a-z]\w*_t\b/,lookbehind:!0},keyword:/\b(?:_Alignas|_Alignof|_Atomic|_Bool|_Complex|_Generic|_Imaginary|_Noreturn|_Static_assert|_Thread_local|__attribute__|asm|auto|break|case|char|const|continue|default|do|double|else|enum|extern|float|for|goto|if|inline|int|long|register|return|short|signed|sizeof|static|struct|switch|typedef|typeof|union|unsigned|void|volatile|while)\b/,function:/\b[a-z_]\w*(?=\s*\()/i,number:/(?:\b0x(?:[\da-f]+(?:\.[\da-f]*)?|\.[\da-f]+)(?:p[+-]?\d+)?|(?:\b\d+(?:\.\d*)?|\B\.\d+)(?:e[+-]?\d+)?)[ful]{0,4}/i,operator:/>>=?|<<=?|->|([-+&|:])\1|[?:~]|[-+*/%&|^!=<>]=?/}),C.languages.insertBefore("c","string",{char:{pattern:/'(?:\\(?:\r\n|[\s\S])|[^'\\\r\n]){0,32}'/,greedy:!0}}),C.languages.insertBefore("c","string",{macro:{pattern:/(^[\t 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C.languages.c.boolean,C.languages.objectivec=C.languages.extend("c",{string:{pattern:/@?"(?:\\(?:\r\n|[\s\S])|[^"\\\r\n])*"/,greedy:!0},keyword:/\b(?:asm|auto|break|case|char|const|continue|default|do|double|else|enum|extern|float|for|goto|if|in|inline|int|long|register|return|self|short|signed|sizeof|static|struct|super|switch|typedef|typeof|union|unsigned|void|volatile|while)\b|(?:@interface|@end|@implementation|@protocol|@class|@public|@protected|@private|@property|@try|@catch|@finally|@throw|@synthesize|@dynamic|@selector)\b/,operator:/-[->]?|\+\+?|!=?|<>?=?|==?|&&?|\|\|?|[~^%?*\/@]/}),delete C.languages.objectivec["class-name"],C.languages.objc=C.languages.objectivec,C.languages.reason=C.languages.extend("clike",{string:{pattern:/"(?:\\(?:\r\n|[\s\S])|[^\\\r\n"])*"/,greedy:!0},"class-name":/\b[A-Z]\w*/,keyword:/\b(?:and|as|assert|begin|class|constraint|do|done|downto|else|end|exception|external|for|fun|function|functor|if|in|include|inherit|initializer|lazy|let|method|module|mutable|new|nonrec|object|of|open|or|private|rec|sig|struct|switch|then|to|try|type|val|virtual|when|while|with)\b/,operator:/\.{3}|:[:=]|\|>|->|=(?:==?|>)?|<=?|>=?|[|^?'#!~`]|[+\-*\/]\.?|\b(?:asr|land|lor|lsl|lsr|lxor|mod)\b/}),C.languages.insertBefore("reason","class-name",{char:{pattern:/'(?:\\x[\da-f]{2}|\\o[0-3][0-7][0-7]|\\\d{3}|\\.|[^'\\\r\n])'/,greedy:!0},constructor:/\b[A-Z]\w*\b(?!\s*\.)/,label:{pattern:/\b[a-z]\w*(?=::)/,alias:"symbol"}}),delete C.languages.reason.function,function(e){for(var t=/\/\*(?:[^*/]|\*(?!\/)|\/(?!\*)|)*\*\//.source,n=0;n<2;n++)t=t.replace(//g,(function(){return t}));t=t.replace(//g,(function(){return/[^\s\S]/.source})),e.languages.rust={comment:[{pattern:RegExp(/(^|[^\\])/.source+t),lookbehind:!0,greedy:!0},{pattern:/(^|[^\\:])\/\/.*/,lookbehind:!0,greedy:!0}],string:{pattern:/b?"(?:\\[\s\S]|[^\\"])*"|b?r(#*)"(?:[^"]|"(?!\1))*"\1/,greedy:!0},char:{pattern:/b?'(?:\\(?:x[0-7][\da-fA-F]|u\{(?:[\da-fA-F]_*){1,6}\}|.)|[^\\\r\n\t'])'/,greedy:!0},attribute:{pattern:/#!?\[(?:[^\[\]"]|"(?:\\[\s\S]|[^\\"])*")*\]/,greedy:!0,alias:"attr-name",inside:{string:null}},"closure-params":{pattern:/([=(,:]\s*|\bmove\s*)\|[^|]*\||\|[^|]*\|(?=\s*(?:\{|->))/,lookbehind:!0,greedy:!0,inside:{"closure-punctuation":{pattern:/^\||\|$/,alias:"punctuation"},rest:null}},"lifetime-annotation":{pattern:/'\w+/,alias:"symbol"},"fragment-specifier":{pattern:/(\$\w+:)[a-z]+/,lookbehind:!0,alias:"punctuation"},variable:/\$\w+/,"function-definition":{pattern:/(\bfn\s+)\w+/,lookbehind:!0,alias:"function"},"type-definition":{pattern:/(\b(?:enum|struct|trait|type|union)\s+)\w+/,lookbehind:!0,alias:"class-name"},"module-declaration":[{pattern:/(\b(?:crate|mod)\s+)[a-z][a-z_\d]*/,lookbehind:!0,alias:"namespace"},{pattern:/(\b(?:crate|self|super)\s*)::\s*[a-z][a-z_\d]*\b(?:\s*::(?:\s*[a-z][a-z_\d]*\s*::)*)?/,lookbehind:!0,alias:"namespace",inside:{punctuation:/::/}}],keyword:[/\b(?:Self|abstract|as|async|await|become|box|break|const|continue|crate|do|dyn|else|enum|extern|final|fn|for|if|impl|in|let|loop|macro|match|mod|move|mut|override|priv|pub|ref|return|self|static|struct|super|trait|try|type|typeof|union|unsafe|unsized|use|virtual|where|while|yield)\b/,/\b(?:bool|char|f(?:32|64)|[ui](?:8|16|32|64|128|size)|str)\b/],function:/\b[a-z_]\w*(?=\s*(?:::\s*<|\())/,macro:{pattern:/\b\w+!/,alias:"property"},constant:/\b[A-Z_][A-Z_\d]+\b/,"class-name":/\b[A-Z]\w*\b/,namespace:{pattern:/(?:\b[a-z][a-z_\d]*\s*::\s*)*\b[a-z][a-z_\d]*\s*::(?!\s*<)/,inside:{punctuation:/::/}},number:/\b(?:0x[\dA-Fa-f](?:_?[\dA-Fa-f])*|0o[0-7](?:_?[0-7])*|0b[01](?:_?[01])*|(?:(?:\d(?:_?\d)*)?\.)?\d(?:_?\d)*(?:[Ee][+-]?\d+)?)(?:_?(?:f32|f64|[iu](?:8|16|32|64|size)?))?\b/,boolean:/\b(?:false|true)\b/,punctuation:/->|\.\.=|\.{1,3}|::|[{}[\];(),:]/,operator:/[-+*\/%!^]=?|=[=>]?|&[&=]?|\|[|=]?|<>?=?|[@?]/},e.languages.rust["closure-params"].inside.rest=e.languages.rust,e.languages.rust.attribute.inside.string=e.languages.rust.string}(C),C.languages.go=C.languages.extend("clike",{string:{pattern:/(^|[^\\])"(?:\\.|[^"\\\r\n])*"|`[^`]*`/,lookbehind:!0,greedy:!0},keyword:/\b(?:break|case|chan|const|continue|default|defer|else|fallthrough|for|func|go(?:to)?|if|import|interface|map|package|range|return|select|struct|switch|type|var)\b/,boolean:/\b(?:_|false|iota|nil|true)\b/,number:[/\b0(?:b[01_]+|o[0-7_]+)i?\b/i,/\b0x(?:[a-f\d_]+(?:\.[a-f\d_]*)?|\.[a-f\d_]+)(?:p[+-]?\d+(?:_\d+)*)?i?(?!\w)/i,/(?:\b\d[\d_]*(?:\.[\d_]*)?|\B\.\d[\d_]*)(?:e[+-]?[\d_]+)?i?(?!\w)/i],operator:/[*\/%^!=]=?|\+[=+]?|-[=-]?|\|[=|]?|&(?:=|&|\^=?)?|>(?:>=?|=)?|<(?:<=?|=|-)?|:=|\.\.\./,builtin:/\b(?:append|bool|byte|cap|close|complex|complex(?:64|128)|copy|delete|error|float(?:32|64)|u?int(?:8|16|32|64)?|imag|len|make|new|panic|print(?:ln)?|real|recover|rune|string|uintptr)\b/}),C.languages.insertBefore("go","string",{char:{pattern:/'(?:\\.|[^'\\\r\n]){0,10}'/,greedy:!0}}),delete C.languages.go["class-name"],function(e){var t=/\b(?:alignas|alignof|asm|auto|bool|break|case|catch|char|char16_t|char32_t|char8_t|class|co_await|co_return|co_yield|compl|concept|const|const_cast|consteval|constexpr|constinit|continue|decltype|default|delete|do|double|dynamic_cast|else|enum|explicit|export|extern|final|float|for|friend|goto|if|import|inline|int|int16_t|int32_t|int64_t|int8_t|long|module|mutable|namespace|new|noexcept|nullptr|operator|override|private|protected|public|register|reinterpret_cast|requires|return|short|signed|sizeof|static|static_assert|static_cast|struct|switch|template|this|thread_local|throw|try|typedef|typeid|typename|uint16_t|uint32_t|uint64_t|uint8_t|union|unsigned|using|virtual|void|volatile|wchar_t|while)\b/,n=/\b(?!)\w+(?:\s*\.\s*\w+)*\b/.source.replace(//g,(function(){return t.source}));e.languages.cpp=e.languages.extend("c",{"class-name":[{pattern:RegExp(/(\b(?:class|concept|enum|struct|typename)\s+)(?!)\w+/.source.replace(//g,(function(){return t.source}))),lookbehind:!0},/\b[A-Z]\w*(?=\s*::\s*\w+\s*\()/,/\b[A-Z_]\w*(?=\s*::\s*~\w+\s*\()/i,/\b\w+(?=\s*<(?:[^<>]|<(?:[^<>]|<[^<>]*>)*>)*>\s*::\s*\w+\s*\()/],keyword:t,number:{pattern:/(?:\b0b[01']+|\b0x(?:[\da-f']+(?:\.[\da-f']*)?|\.[\da-f']+)(?:p[+-]?[\d']+)?|(?:\b[\d']+(?:\.[\d']*)?|\B\.[\d']+)(?:e[+-]?[\d']+)?)[ful]{0,4}/i,greedy:!0},operator:/>>=?|<<=?|->|--|\+\+|&&|\|\||[?:~]|<=>|[-+*/%&|^!=<>]=?|\b(?:and|and_eq|bitand|bitor|not|not_eq|or|or_eq|xor|xor_eq)\b/,boolean:/\b(?:false|true)\b/}),e.languages.insertBefore("cpp","string",{module:{pattern:RegExp(/(\b(?:import|module)\s+)/.source+"(?:"+/"(?:\\(?:\r\n|[\s\S])|[^"\\\r\n])*"|<[^<>\r\n]*>/.source+"|"+/(?:\s*:\s*)?|:\s*/.source.replace(//g,(function(){return n}))+")"),lookbehind:!0,greedy:!0,inside:{string:/^[<"][\s\S]+/,operator:/:/,punctuation:/\./}},"raw-string":{pattern:/R"([^()\\ 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e.content?e.content:e.content.map(s).join(""):""};e.hooks.add("after-tokenize",(function(e){"jsx"!==e.language&&"tsx"!==e.language||i(e.tokens)}))}(C),function(e){var t=e.util.clone(e.languages.typescript);(t=(e.languages.tsx=e.languages.extend("jsx",t),delete e.languages.tsx.parameter,delete 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e.languages.kotlin["class-name"];var t={"interpolation-punctuation":{pattern:/^\$\{?|\}$/,alias:"punctuation"},expression:{pattern:/[\s\S]+/,inside:e.languages.kotlin}};e.languages.insertBefore("kotlin","string",{"string-literal":[{pattern:/"""(?:[^$]|\$(?:(?!\{)|\{[^{}]*\}))*?"""/,alias:"multiline",inside:{interpolation:{pattern:/\$(?:[a-z_]\w*|\{[^{}]*\})/i,inside:t},string:/[\s\S]+/}},{pattern:/"(?:[^"\\\r\n$]|\\.|\$(?:(?!\{)|\{[^{}]*\}))*"/,alias:"singleline",inside:{interpolation:{pattern:/((?:^|[^\\])(?:\\{2})*)\$(?:[a-z_]\w*|\{[^{}]*\})/i,lookbehind:!0,inside:t},string:/[\s\S]+/}}],char:{pattern:/'(?:[^'\\\r\n]|\\(?:.|u[a-fA-F0-9]{0,4}))'/,greedy:!0}}),delete e.languages.kotlin.string,e.languages.insertBefore("kotlin","keyword",{annotation:{pattern:/\B@(?:\w+:)?(?:[A-Z]\w*|\[[^\]]+\])/,alias:"builtin"}}),e.languages.insertBefore("kotlin","function",{label:{pattern:/\b\w+@|@\w+\b/,alias:"symbol"}}),e.languages.kt=e.languages.kotlin,e.languages.kts=e.languages.kotlin}(C),C.languages.c=C.languages.extend("clike",{comment:{pattern:/\/\/(?:[^\r\n\\]|\\(?:\r\n?|\n|(?![\r\n])))*|\/\*[\s\S]*?(?:\*\/|$)/,greedy:!0},string:{pattern:/"(?:\\(?:\r\n|[\s\S])|[^"\\\r\n])*"/,greedy:!0},"class-name":{pattern:/(\b(?:enum|struct)\s+(?:__attribute__\s*\(\([\s\S]*?\)\)\s*)?)\w+|\b[a-z]\w*_t\b/,lookbehind:!0},keyword:/\b(?:_Alignas|_Alignof|_Atomic|_Bool|_Complex|_Generic|_Imaginary|_Noreturn|_Static_assert|_Thread_local|__attribute__|asm|auto|break|case|char|const|continue|default|do|double|else|enum|extern|float|for|goto|if|inline|int|long|register|return|short|signed|sizeof|static|struct|switch|typedef|typeof|union|unsigned|void|volatile|while)\b/,function:/\b[a-z_]\w*(?=\s*\()/i,number:/(?:\b0x(?:[\da-f]+(?:\.[\da-f]*)?|\.[\da-f]+)(?:p[+-]?\d+)?|(?:\b\d+(?:\.\d*)?|\B\.\d+)(?:e[+-]?\d+)?)[ful]{0,4}/i,operator:/>>=?|<<=?|->|([-+&|:])\1|[?:~]|[-+*/%&|^!=<>]=?/}),C.languages.insertBefore("c","string",{char:{pattern:/'(?:\\(?:\r\n|[\s\S])|[^'\\\r\n]){0,32}'/,greedy:!0}}),C.languages.insertBefore("c","string",{macro:{pattern:/(^[\t 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C.languages.c.boolean,C.languages.objectivec=C.languages.extend("c",{string:{pattern:/@?"(?:\\(?:\r\n|[\s\S])|[^"\\\r\n])*"/,greedy:!0},keyword:/\b(?:asm|auto|break|case|char|const|continue|default|do|double|else|enum|extern|float|for|goto|if|in|inline|int|long|register|return|self|short|signed|sizeof|static|struct|super|switch|typedef|typeof|union|unsigned|void|volatile|while)\b|(?:@interface|@end|@implementation|@protocol|@class|@public|@protected|@private|@property|@try|@catch|@finally|@throw|@synthesize|@dynamic|@selector)\b/,operator:/-[->]?|\+\+?|!=?|<>?=?|==?|&&?|\|\|?|[~^%?*\/@]/}),delete C.languages.objectivec["class-name"],C.languages.objc=C.languages.objectivec,C.languages.reason=C.languages.extend("clike",{string:{pattern:/"(?:\\(?:\r\n|[\s\S])|[^\\\r\n"])*"/,greedy:!0},"class-name":/\b[A-Z]\w*/,keyword:/\b(?:and|as|assert|begin|class|constraint|do|done|downto|else|end|exception|external|for|fun|function|functor|if|in|include|inherit|initializer|lazy|let|method|module|mutable|new|nonrec|object|of|open|or|private|rec|sig|struct|switch|then|to|try|type|val|virtual|when|while|with)\b/,operator:/\.{3}|:[:=]|\|>|->|=(?:==?|>)?|<=?|>=?|[|^?'#!~`]|[+\-*\/]\.?|\b(?:asr|land|lor|lsl|lsr|lxor|mod)\b/}),C.languages.insertBefore("reason","class-name",{char:{pattern:/'(?:\\x[\da-f]{2}|\\o[0-3][0-7][0-7]|\\\d{3}|\\.|[^'\\\r\n])'/,greedy:!0},constructor:/\b[A-Z]\w*\b(?!\s*\.)/,label:{pattern:/\b[a-z]\w*(?=::)/,alias:"symbol"}}),delete C.languages.reason.function,function(e){for(var t=/\/\*(?:[^*/]|\*(?!\/)|\/(?!\*)|)*\*\//.source,n=0;n<2;n++)t=t.replace(//g,(function(){return t}));t=t.replace(//g,(function(){return/[^\s\S]/.source})),e.languages.rust={comment:[{pattern:RegExp(/(^|[^\\])/.source+t),lookbehind:!0,greedy:!0},{pattern:/(^|[^\\:])\/\/.*/,lookbehind:!0,greedy:!0}],string:{pattern:/b?"(?:\\[\s\S]|[^\\"])*"|b?r(#*)"(?:[^"]|"(?!\1))*"\1/,greedy:!0},char:{pattern:/b?'(?:\\(?:x[0-7][\da-fA-F]|u\{(?:[\da-fA-F]_*){1,6}\}|.)|[^\\\r\n\t'])'/,greedy:!0},attribute:{pattern:/#!?\[(?:[^\[\]"]|"(?:\\[\s\S]|[^\\"])*")*\]/,greedy:!0,alias:"attr-name",inside:{string:null}},"closure-params":{pattern:/([=(,:]\s*|\bmove\s*)\|[^|]*\||\|[^|]*\|(?=\s*(?:\{|->))/,lookbehind:!0,greedy:!0,inside:{"closure-punctuation":{pattern:/^\||\|$/,alias:"punctuation"},rest:null}},"lifetime-annotation":{pattern:/'\w+/,alias:"symbol"},"fragment-specifier":{pattern:/(\$\w+:)[a-z]+/,lookbehind:!0,alias:"punctuation"},variable:/\$\w+/,"function-definition":{pattern:/(\bfn\s+)\w+/,lookbehind:!0,alias:"function"},"type-definition":{pattern:/(\b(?:enum|struct|trait|type|union)\s+)\w+/,lookbehind:!0,alias:"class-name"},"module-declaration":[{pattern:/(\b(?:crate|mod)\s+)[a-z][a-z_\d]*/,lookbehind:!0,alias:"namespace"},{pattern:/(\b(?:crate|self|super)\s*)::\s*[a-z][a-z_\d]*\b(?:\s*::(?:\s*[a-z][a-z_\d]*\s*::)*)?/,lookbehind:!0,alias:"namespace",inside:{punctuation:/::/}}],keyword:[/\b(?:Self|abstract|as|async|await|become|box|break|const|continue|crate|do|dyn|else|enum|extern|final|fn|for|if|impl|in|let|loop|macro|match|mod|move|mut|override|priv|pub|ref|return|self|static|struct|super|trait|try|type|typeof|union|unsafe|unsized|use|virtual|where|while|yield)\b/,/\b(?:bool|char|f(?:32|64)|[ui](?:8|16|32|64|128|size)|str)\b/],function:/\b[a-z_]\w*(?=\s*(?:::\s*<|\())/,macro:{pattern:/\b\w+!/,alias:"property"},constant:/\b[A-Z_][A-Z_\d]+\b/,"class-name":/\b[A-Z]\w*\b/,namespace:{pattern:/(?:\b[a-z][a-z_\d]*\s*::\s*)*\b[a-z][a-z_\d]*\s*::(?!\s*<)/,inside:{punctuation:/::/}},number:/\b(?:0x[\dA-Fa-f](?:_?[\dA-Fa-f])*|0o[0-7](?:_?[0-7])*|0b[01](?:_?[01])*|(?:(?:\d(?:_?\d)*)?\.)?\d(?:_?\d)*(?:[Ee][+-]?\d+)?)(?:_?(?:f32|f64|[iu](?:8|16|32|64|size)?))?\b/,boolean:/\b(?:false|true)\b/,punctuation:/->|\.\.=|\.{1,3}|::|[{}[\];(),:]/,operator:/[-+*\/%!^]=?|=[=>]?|&[&=]?|\|[|=]?|<>?=?|[@?]/},e.languages.rust["closure-params"].inside.rest=e.languages.rust,e.languages.rust.attribute.inside.string=e.languages.rust.string}(C),C.languages.go=C.languages.extend("clike",{string:{pattern:/(^|[^\\])"(?:\\.|[^"\\\r\n])*"|`[^`]*`/,lookbehind:!0,greedy:!0},keyword:/\b(?:break|case|chan|const|continue|default|defer|else|fallthrough|for|func|go(?:to)?|if|import|interface|map|package|range|return|select|struct|switch|type|var)\b/,boolean:/\b(?:_|false|iota|nil|true)\b/,number:[/\b0(?:b[01_]+|o[0-7_]+)i?\b/i,/\b0x(?:[a-f\d_]+(?:\.[a-f\d_]*)?|\.[a-f\d_]+)(?:p[+-]?\d+(?:_\d+)*)?i?(?!\w)/i,/(?:\b\d[\d_]*(?:\.[\d_]*)?|\B\.\d[\d_]*)(?:e[+-]?[\d_]+)?i?(?!\w)/i],operator:/[*\/%^!=]=?|\+[=+]?|-[=-]?|\|[=|]?|&(?:=|&|\^=?)?|>(?:>=?|=)?|<(?:<=?|=|-)?|:=|\.\.\./,builtin:/\b(?:append|bool|byte|cap|close|complex|complex(?:64|128)|copy|delete|error|float(?:32|64)|u?int(?:8|16|32|64)?|imag|len|make|new|panic|print(?:ln)?|real|recover|rune|string|uintptr)\b/}),C.languages.insertBefore("go","string",{char:{pattern:/'(?:\\.|[^'\\\r\n]){0,10}'/,greedy:!0}}),delete C.languages.go["class-name"],function(e){var t=/\b(?:alignas|alignof|asm|auto|bool|break|case|catch|char|char16_t|char32_t|char8_t|class|co_await|co_return|co_yield|compl|concept|const|const_cast|consteval|constexpr|constinit|continue|decltype|default|delete|do|double|dynamic_cast|else|enum|explicit|export|extern|final|float|for|friend|goto|if|import|inline|int|int16_t|int32_t|int64_t|int8_t|long|module|mutable|namespace|new|noexcept|nullptr|operator|override|private|protected|public|register|reinterpret_cast|requires|return|short|signed|sizeof|static|static_assert|static_cast|struct|switch|template|this|thread_local|throw|try|typedef|typeid|typename|uint16_t|uint32_t|uint64_t|uint8_t|union|unsigned|using|virtual|void|volatile|wchar_t|while)\b/,n=/\b(?!)\w+(?:\s*\.\s*\w+)*\b/.source.replace(//g,(function(){return t.source}));e.languages.cpp=e.languages.extend("c",{"class-name":[{pattern:RegExp(/(\b(?:class|concept|enum|struct|typename)\s+)(?!)\w+/.source.replace(//g,(function(){return t.source}))),lookbehind:!0},/\b[A-Z]\w*(?=\s*::\s*\w+\s*\()/,/\b[A-Z_]\w*(?=\s*::\s*~\w+\s*\()/i,/\b\w+(?=\s*<(?:[^<>]|<(?:[^<>]|<[^<>]*>)*>)*>\s*::\s*\w+\s*\()/],keyword:t,number:{pattern:/(?:\b0b[01']+|\b0x(?:[\da-f']+(?:\.[\da-f']*)?|\.[\da-f']+)(?:p[+-]?[\d']+)?|(?:\b[\d']+(?:\.[\d']*)?|\B\.[\d']+)(?:e[+-]?[\d']+)?)[ful]{0,4}/i,greedy:!0},operator:/>>=?|<<=?|->|--|\+\+|&&|\|\||[?:~]|<=>|[-+*/%&|^!=<>]=?|\b(?:and|and_eq|bitand|bitor|not|not_eq|or|or_eq|xor|xor_eq)\b/,boolean:/\b(?:false|true)\b/}),e.languages.insertBefore("cpp","string",{module:{pattern:RegExp(/(\b(?:import|module)\s+)/.source+"(?:"+/"(?:\\(?:\r\n|[\s\S])|[^"\\\r\n])*"|<[^<>\r\n]*>/.source+"|"+/(?:\s*:\s*)?|:\s*/.source.replace(//g,(function(){return n}))+")"),lookbehind:!0,greedy:!0,inside:{string:/^[<"][\s\S]+/,operator:/:/,punctuation:/\./}},"raw-string":{pattern:/R"([^()\\ 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Day 21 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today I study about about Machine Learning, specifically about the K-Means Clustering Algorithm, you can see my notes here, and the code here.

diff --git a/blog/archive.html b/blog/archive.html index f2eeab04..eee6f9e4 100644 --- a/blog/archive.html +++ b/blog/archive.html @@ -9,8 +9,8 @@ - - + +

Archive

Archive

2023​

diff --git a/blog/day-1-100-days-of-code.html b/blog/day-1-100-days-of-code.html index b0a1d604..27866e64 100644 --- a/blog/day-1-100-days-of-code.html +++ b/blog/day-1-100-days-of-code.html @@ -9,8 +9,8 @@ - - + +

Day 1 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today I started studying Go by doing the exercises in the repository of @wagslane fcc-learn-golang-assets.

diff --git a/blog/day-10-100-days-of-code.html b/blog/day-10-100-days-of-code.html index 452c2691..e3122c01 100644 --- a/blog/day-10-100-days-of-code.html +++ b/blog/day-10-100-days-of-code.html @@ -9,8 +9,8 @@ - - + +

Day 10 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today I studied about the Object Relational Database using Oracle DB to a exam that I have tomorrow.

diff --git a/blog/day-11-100-days-of-code.html b/blog/day-11-100-days-of-code.html index f9c0372b..97166b51 100644 --- a/blog/day-11-100-days-of-code.html +++ b/blog/day-11-100-days-of-code.html @@ -9,8 +9,8 @@ - - + +

Day 11 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today I continue to study about the Object Relational Database using Oracle DB to a exam that I had at afternoon.

diff --git a/blog/day-12-100-days-of-code.html b/blog/day-12-100-days-of-code.html index cbb47940..d23f879c 100644 --- a/blog/day-12-100-days-of-code.html +++ b/blog/day-12-100-days-of-code.html @@ -9,8 +9,8 @@ - - + +

Day 12 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today I start to integrate Supabase to my project using the expo, I also learn about the new expo router and how to use it.

diff --git a/blog/day-13-100-days-of-code.html b/blog/day-13-100-days-of-code.html index 14ff70a9..b365bacb 100644 --- a/blog/day-13-100-days-of-code.html +++ b/blog/day-13-100-days-of-code.html @@ -9,8 +9,8 @@ - - + +

Day 13 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today I continue to implements the Supabase to my project, I also learn about the new expo router and how to use it.

diff --git a/blog/day-14-100-days-of-code.html b/blog/day-14-100-days-of-code.html index 6825ea94..8a27037f 100644 --- a/blog/day-14-100-days-of-code.html +++ b/blog/day-14-100-days-of-code.html @@ -9,8 +9,8 @@ - - + +

Day 14 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today I start to solve a colab notebook from college. In this notebook, I use the pandas library to read a csv file and do some data analysis. The dataset that I used was this. The focus of this notebook was to use the plotly library to create some graphs.

diff --git a/blog/day-15-100-days-of-code.html b/blog/day-15-100-days-of-code.html index 3d5f71e3..afb3bcb0 100644 --- a/blog/day-15-100-days-of-code.html +++ b/blog/day-15-100-days-of-code.html @@ -9,8 +9,8 @@ - - + +

Day 15 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today I start to build a prof of concept to test some concepts like Idempotency, Batch Processing, Circuit Breaker, background jobs, and message queues. I build this project relearn how to configure node with typescript and build the project with Dockerfile and run a infra local with docker-compose. Here you can see the source code. Alongside I start to learn more about IPC (Inter-Process Communication).

diff --git a/blog/day-16-100-days-of-code.html b/blog/day-16-100-days-of-code.html index faf32201..28e16c35 100644 --- a/blog/day-16-100-days-of-code.html +++ b/blog/day-16-100-days-of-code.html @@ -9,8 +9,8 @@ - - + +

Day 16 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today at work I had to start to study a legacy code that I will work with new features soon, to make my life more easy I start doing some this:

diff --git a/blog/day-17-100-days-of-code.html b/blog/day-17-100-days-of-code.html index abb11dfc..52209e37 100644 --- a/blog/day-17-100-days-of-code.html +++ b/blog/day-17-100-days-of-code.html @@ -9,8 +9,8 @@ - - + +

Day 17 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today I continue to implement a project to college using expo, expo router, zustand e supabase. I'm using this project to learn more about this technologies and to test some concepts. I will start to write some test cause I want to learn more about testing in react native.

diff --git a/blog/day-18-100-days-of-code.html b/blog/day-18-100-days-of-code.html index ca53448e..e89544e6 100644 --- a/blog/day-18-100-days-of-code.html +++ b/blog/day-18-100-days-of-code.html @@ -9,8 +9,8 @@ - - + +

Day 18 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today I refactor some screen of the app that I'm building to study some concepts, I'm using expo, expo router, zustand e supabase. I'm using this project to learn more about this technologies and to test some concepts. I will start to write some test cause I want to learn more about testing in react native.

diff --git a/blog/day-19-100-days-of-code.html b/blog/day-19-100-days-of-code.html index 8306bd29..3a86bf33 100644 --- a/blog/day-19-100-days-of-code.html +++ b/blog/day-19-100-days-of-code.html @@ -9,8 +9,8 @@ - - + +

Day 19 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

So today is my birthday, so I work on something special, today with my friends I build a minecraft modpack and buy a host to upload a minecraft server, so I spend all day building the server and configuring the mods.

diff --git a/blog/day-2-100-days-of-code.html b/blog/day-2-100-days-of-code.html index 6214f18e..7a570ac4 100644 --- a/blog/day-2-100-days-of-code.html +++ b/blog/day-2-100-days-of-code.html @@ -9,8 +9,8 @@ - - + +

Day 2 of 100 Days of Code

· 2 min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today was a really full day of work, I have been working to finish a project that I have been working on for a while from the company that I work for, so I didn't have much time to code, but I managed to do some things.

diff --git a/blog/day-20-100-days-of-code.html b/blog/day-20-100-days-of-code.html index 3da3865d..87ec5921 100644 --- a/blog/day-20-100-days-of-code.html +++ b/blog/day-20-100-days-of-code.html @@ -9,8 +9,8 @@ - - + +

Day 20 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today was my rest day and I only study a little about some algorithms that I learn on college.

diff --git a/blog/day-21-100-days-of-code.html b/blog/day-21-100-days-of-code.html index 0ab260aa..c20f73e1 100644 --- a/blog/day-21-100-days-of-code.html +++ b/blog/day-21-100-days-of-code.html @@ -9,8 +9,8 @@ - - + +

Day 21 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today I study about about Machine Learning, specifically about the K-Means Clustering Algorithm, you can see my notes here, and the code here.

diff --git a/blog/day-22-100-days-of-code.html b/blog/day-22-100-days-of-code.html index ee922ea1..f1924d29 100644 --- a/blog/day-22-100-days-of-code.html +++ b/blog/day-22-100-days-of-code.html @@ -9,8 +9,8 @@ - - + +

Day 22 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today I study about the Silhouette Analysis, this is based on generate a metric to validate the correctness of a clustering algorithm. You can see my notes here.

diff --git a/blog/day-3-100-days-of-code.html b/blog/day-3-100-days-of-code.html index c8a9e0dc..31fadcd9 100644 --- a/blog/day-3-100-days-of-code.html +++ b/blog/day-3-100-days-of-code.html @@ -9,8 +9,8 @@ - - + +

Day 3 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today I finished the second lab for my Data Science class, I used Pandas and Seaborn library to plot some histograms and boxplots, maybe I would write a post about it soon. You can check the notebook here.

diff --git a/blog/day-4-100-days-of-code.html b/blog/day-4-100-days-of-code.html index 3e0760a1..45b3d530 100644 --- a/blog/day-4-100-days-of-code.html +++ b/blog/day-4-100-days-of-code.html @@ -9,8 +9,8 @@ - - + +

Day 4 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today I was very busy with work and college, but I managed to study, so I see this topics today:

diff --git a/blog/day-5-100-days-of-code.html b/blog/day-5-100-days-of-code.html index 28ad61c4..609d7daa 100644 --- a/blog/day-5-100-days-of-code.html +++ b/blog/day-5-100-days-of-code.html @@ -9,8 +9,8 @@ - - + +

Day 5 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today was nice, I study lot of things and at the end of the day I release a game!

diff --git a/blog/day-6-100-days-of-code.html b/blog/day-6-100-days-of-code.html index b99f2ac2..cef47a5d 100644 --- a/blog/day-6-100-days-of-code.html +++ b/blog/day-6-100-days-of-code.html @@ -9,8 +9,8 @@ - - + +

Day 6 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today was a slow day for me, I can't concentrate to study, but I do some things.

diff --git a/blog/day-7-100-days-of-code.html b/blog/day-7-100-days-of-code.html index afd622ef..e2159eac 100644 --- a/blog/day-7-100-days-of-code.html +++ b/blog/day-7-100-days-of-code.html @@ -9,8 +9,8 @@ - - + +

Day 7 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today was a day to rest, but I study a little bit of ODB. I did some exercicies that my professor gave me. You can see here

diff --git a/blog/day-8-100-days-of-code.html b/blog/day-8-100-days-of-code.html index 32c46196..bed92d66 100644 --- a/blog/day-8-100-days-of-code.html +++ b/blog/day-8-100-days-of-code.html @@ -9,8 +9,8 @@ - - + +

Day 8 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today I had a Data Science class and I learned about correlation.You can see my notes here, they are incomplete but at the end of this week I will complete them whem reviewing the content to work on a dataset that I had to finish until thursday.

diff --git a/blog/day-9-100-days-of-code.html b/blog/day-9-100-days-of-code.html index ef185648..ece18e48 100644 --- a/blog/day-9-100-days-of-code.html +++ b/blog/day-9-100-days-of-code.html @@ -9,8 +9,8 @@ - - + +

Day 9 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today was a hard, I had to update the typescript of a old project so I had to study about the typescript module resolution and the tsconfig.json file.

diff --git a/blog/how-to-code-everyday.html b/blog/how-to-code-everyday.html index 1b738b7f..3fb91633 100644 --- a/blog/how-to-code-everyday.html +++ b/blog/how-to-code-everyday.html @@ -9,8 +9,8 @@ - - + +

How to Code Everyday

· 2 min read
Paulo Hernane
Paulo Hernane
Software Engineer

Code is a skill that you need to practice every day. But some days we don't are in the mood to code, but we fell anxious about it. So, I will share with you some tips that I use to code every day.

diff --git a/blog/page/2.html b/blog/page/2.html index 8ef71d78..78547e78 100644 --- a/blog/page/2.html +++ b/blog/page/2.html @@ -9,8 +9,8 @@ - - + +

Day 12 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today I start to integrate Supabase to my project using the expo, I also learn about the new expo router and how to use it.

diff --git a/blog/page/3.html b/blog/page/3.html index c616ad7b..12e0c40c 100644 --- a/blog/page/3.html +++ b/blog/page/3.html @@ -9,8 +9,8 @@ - - + +

Day 2 of 100 Days of Code

· 2 min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today was a really full day of work, I have been working to finish a project that I have been working on for a while from the company that I work for, so I didn't have much time to code, but I managed to do some things.

diff --git a/blog/tags.html b/blog/tags.html index 87d23bb2..6bd07335 100644 --- a/blog/tags.html +++ b/blog/tags.html @@ -9,8 +9,8 @@ - - + +

Tags

diff --git a/blog/tags/100-days-of-code.html b/blog/tags/100-days-of-code.html index 752546e7..94612b15 100644 --- a/blog/tags/100-days-of-code.html +++ b/blog/tags/100-days-of-code.html @@ -9,8 +9,8 @@ - - + +

22 posts tagged with "100DaysOfCode"

View All Tags

Day 21 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today I study about about Machine Learning, specifically about the K-Means Clustering Algorithm, you can see my notes here, and the code here.

diff --git a/blog/tags/100-days-of-code/page/2.html b/blog/tags/100-days-of-code/page/2.html index 16659be6..4c28916e 100644 --- a/blog/tags/100-days-of-code/page/2.html +++ b/blog/tags/100-days-of-code/page/2.html @@ -9,8 +9,8 @@ - - + +

22 posts tagged with "100DaysOfCode"

View All Tags

Day 12 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today I start to integrate Supabase to my project using the expo, I also learn about the new expo router and how to use it.

diff --git a/blog/tags/100-days-of-code/page/3.html b/blog/tags/100-days-of-code/page/3.html index 2d42eecd..0a2b23e8 100644 --- a/blog/tags/100-days-of-code/page/3.html +++ b/blog/tags/100-days-of-code/page/3.html @@ -9,8 +9,8 @@ - - + +

22 posts tagged with "100DaysOfCode"

View All Tags

Day 2 of 100 Days of Code

· 2 min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today was a really full day of work, I have been working to finish a project that I have been working on for a while from the company that I work for, so I didn't have much time to code, but I managed to do some things.

diff --git a/blog/tags/code.html b/blog/tags/code.html index c0526288..a898acb4 100644 --- a/blog/tags/code.html +++ b/blog/tags/code.html @@ -9,8 +9,8 @@ - - + +

One post tagged with "code"

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How to Code Everyday

· 2 min read
Paulo Hernane
Paulo Hernane
Software Engineer

Code is a skill that you need to practice every day. But some days we don't are in the mood to code, but we fell anxious about it. So, I will share with you some tips that I use to code every day.

diff --git a/blog/tags/concurrency.html b/blog/tags/concurrency.html index d25b05d7..0ac60383 100644 --- a/blog/tags/concurrency.html +++ b/blog/tags/concurrency.html @@ -9,8 +9,8 @@ - - + +

One post tagged with "Concurrency"

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Day 6 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today was a slow day for me, I can't concentrate to study, but I do some things.

diff --git a/blog/tags/concurrent-programming.html b/blog/tags/concurrent-programming.html index 305b9511..91995ac0 100644 --- a/blog/tags/concurrent-programming.html +++ b/blog/tags/concurrent-programming.html @@ -9,8 +9,8 @@ - - + +

2 posts tagged with "Concurrent Programming"

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Day 6 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today was a slow day for me, I can't concentrate to study, but I do some things.

diff --git a/blog/tags/data-science.html b/blog/tags/data-science.html index 0630b421..b6e99167 100644 --- a/blog/tags/data-science.html +++ b/blog/tags/data-science.html @@ -9,8 +9,8 @@ - - + +

4 posts tagged with "DataScience"

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Day 8 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today I had a Data Science class and I learned about correlation.You can see my notes here, they are incomplete but at the end of this week I will complete them whem reviewing the content to work on a dataset that I had to finish until thursday.

diff --git a/blog/tags/data-structures.html b/blog/tags/data-structures.html index dde76b89..ae709410 100644 --- a/blog/tags/data-structures.html +++ b/blog/tags/data-structures.html @@ -9,8 +9,8 @@ - - + +

One post tagged with "Data Structures"

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Day 2 of 100 Days of Code

· 2 min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today was a really full day of work, I have been working to finish a project that I have been working on for a while from the company that I work for, so I didn't have much time to code, but I managed to do some things.

diff --git a/blog/tags/database.html b/blog/tags/database.html index 969737a4..f8374158 100644 --- a/blog/tags/database.html +++ b/blog/tags/database.html @@ -9,8 +9,8 @@ - - + +

One post tagged with "Database"

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Day 7 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today was a day to rest, but I study a little bit of ODB. I did some exercicies that my professor gave me. You can see here

diff --git a/blog/tags/db.html b/blog/tags/db.html index 4b4e67cc..963ed5f5 100644 --- a/blog/tags/db.html +++ b/blog/tags/db.html @@ -9,8 +9,8 @@ - - + +

2 posts tagged with "DB"

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Day 11 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today I continue to study about the Object Relational Database using Oracle DB to a exam that I had at afternoon.

diff --git a/blog/tags/distributed-systems.html b/blog/tags/distributed-systems.html index 5785760e..ebfaac71 100644 --- a/blog/tags/distributed-systems.html +++ b/blog/tags/distributed-systems.html @@ -9,8 +9,8 @@ - - + +

2 posts tagged with "Distributed Systems"

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Day 9 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today was a hard, I had to update the typescript of a old project so I had to study about the typescript module resolution and the tsconfig.json file.

diff --git a/blog/tags/english.html b/blog/tags/english.html index db608cf9..d6229d3e 100644 --- a/blog/tags/english.html +++ b/blog/tags/english.html @@ -9,8 +9,8 @@ - - + +

6 posts tagged with "English"

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Day 7 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today was a day to rest, but I study a little bit of ODB. I did some exercicies that my professor gave me. You can see here

diff --git a/blog/tags/es-lint.html b/blog/tags/es-lint.html index 4db151e4..a857b112 100644 --- a/blog/tags/es-lint.html +++ b/blog/tags/es-lint.html @@ -9,8 +9,8 @@ - - + +

One post tagged with "ESLint"

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Day 4 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today I was very busy with work and college, but I managed to study, so I see this topics today:

diff --git a/blog/tags/expo.html b/blog/tags/expo.html index 72d56eb2..63109b2b 100644 --- a/blog/tags/expo.html +++ b/blog/tags/expo.html @@ -9,8 +9,8 @@ - - + +

One post tagged with "Expo"

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Day 11 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today I continue to study about the Object Relational Database using Oracle DB to a exam that I had at afternoon.

diff --git a/blog/tags/functions.html b/blog/tags/functions.html index ddbb17d5..8a11ed6f 100644 --- a/blog/tags/functions.html +++ b/blog/tags/functions.html @@ -9,8 +9,8 @@ - - + +

2 posts tagged with "Functions"

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Day 11 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today I continue to study about the Object Relational Database using Oracle DB to a exam that I had at afternoon.

diff --git a/blog/tags/go.html b/blog/tags/go.html index 2df69f2b..63575d1f 100644 --- a/blog/tags/go.html +++ b/blog/tags/go.html @@ -9,8 +9,8 @@ - - + +

2 posts tagged with "go"

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Day 6 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today was a slow day for me, I can't concentrate to study, but I do some things.

diff --git a/blog/tags/godot.html b/blog/tags/godot.html index 1b11fbad..c9560a07 100644 --- a/blog/tags/godot.html +++ b/blog/tags/godot.html @@ -9,8 +9,8 @@ - - + +

One post tagged with "Godot"

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Day 5 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today was nice, I study lot of things and at the end of the day I release a game!

diff --git a/blog/tags/methods.html b/blog/tags/methods.html index 4ca638db..13f12cd7 100644 --- a/blog/tags/methods.html +++ b/blog/tags/methods.html @@ -9,8 +9,8 @@ - - + +

2 posts tagged with "Methods"

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Day 11 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today I continue to study about the Object Relational Database using Oracle DB to a exam that I had at afternoon.

diff --git a/blog/tags/nested-tables.html b/blog/tags/nested-tables.html index 5dad05f3..2f0ba58f 100644 --- a/blog/tags/nested-tables.html +++ b/blog/tags/nested-tables.html @@ -9,8 +9,8 @@ - - + +

2 posts tagged with "Nested Tables"

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Day 11 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today I continue to study about the Object Relational Database using Oracle DB to a exam that I had at afternoon.

diff --git a/blog/tags/next-js.html b/blog/tags/next-js.html index 2158dc8e..a1039712 100644 --- a/blog/tags/next-js.html +++ b/blog/tags/next-js.html @@ -9,8 +9,8 @@ - - + +

One post tagged with "Next.js"

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Day 2 of 100 Days of Code

· 2 min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today was a really full day of work, I have been working to finish a project that I have been working on for a while from the company that I work for, so I didn't have much time to code, but I managed to do some things.

diff --git a/blog/tags/node-js.html b/blog/tags/node-js.html index 38a3c211..c49f7aa7 100644 --- a/blog/tags/node-js.html +++ b/blog/tags/node-js.html @@ -9,8 +9,8 @@ - - + +

One post tagged with "NodeJS"

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Day 4 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today I was very busy with work and college, but I managed to study, so I see this topics today:

diff --git a/blog/tags/object-relational-database.html b/blog/tags/object-relational-database.html index 46eed933..1a100021 100644 --- a/blog/tags/object-relational-database.html +++ b/blog/tags/object-relational-database.html @@ -9,8 +9,8 @@ - - + +

2 posts tagged with "Object Relational Database"

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Day 11 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today I continue to study about the Object Relational Database using Oracle DB to a exam that I had at afternoon.

diff --git a/blog/tags/object-tables.html b/blog/tags/object-tables.html index 8fcb1f22..fc6a966a 100644 --- a/blog/tags/object-tables.html +++ b/blog/tags/object-tables.html @@ -9,8 +9,8 @@ - - + +

2 posts tagged with "Object Tables"

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Day 11 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today I continue to study about the Object Relational Database using Oracle DB to a exam that I had at afternoon.

diff --git a/blog/tags/object-types.html b/blog/tags/object-types.html index bc1e34fe..eb874259 100644 --- a/blog/tags/object-types.html +++ b/blog/tags/object-types.html @@ -9,8 +9,8 @@ - - + +

2 posts tagged with "Object Types"

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Day 11 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today I continue to study about the Object Relational Database using Oracle DB to a exam that I had at afternoon.

diff --git a/blog/tags/odb.html b/blog/tags/odb.html index 34954c00..81667c00 100644 --- a/blog/tags/odb.html +++ b/blog/tags/odb.html @@ -9,8 +9,8 @@ - - + +

3 posts tagged with "ODB"

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Day 11 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today I continue to study about the Object Relational Database using Oracle DB to a exam that I had at afternoon.

diff --git a/blog/tags/oracle.html b/blog/tags/oracle.html index ef3052f5..f8243c78 100644 --- a/blog/tags/oracle.html +++ b/blog/tags/oracle.html @@ -9,8 +9,8 @@ - - + +

3 posts tagged with "Oracle"

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Day 11 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today I continue to study about the Object Relational Database using Oracle DB to a exam that I had at afternoon.

diff --git a/blog/tags/ord.html b/blog/tags/ord.html index 4918ea0e..3d4a1a34 100644 --- a/blog/tags/ord.html +++ b/blog/tags/ord.html @@ -9,8 +9,8 @@ - - + +

One post tagged with "ORD"

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Day 5 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today was nice, I study lot of things and at the end of the day I release a game!

diff --git a/blog/tags/pandas.html b/blog/tags/pandas.html index 9fa890d9..6e22d2a2 100644 --- a/blog/tags/pandas.html +++ b/blog/tags/pandas.html @@ -9,8 +9,8 @@ - - + +

One post tagged with "Pandas"

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Day 3 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today I finished the second lab for my Data Science class, I used Pandas and Seaborn library to plot some histograms and boxplots, maybe I would write a post about it soon. You can check the notebook here.

diff --git a/blog/tags/parallelism.html b/blog/tags/parallelism.html index 11dd61ed..7536b851 100644 --- a/blog/tags/parallelism.html +++ b/blog/tags/parallelism.html @@ -9,8 +9,8 @@ - - + +

One post tagged with "Parallelism"

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Day 6 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today was a slow day for me, I can't concentrate to study, but I do some things.

diff --git a/blog/tags/prettier.html b/blog/tags/prettier.html index b5a3e010..02dcc861 100644 --- a/blog/tags/prettier.html +++ b/blog/tags/prettier.html @@ -9,8 +9,8 @@ - - + +

One post tagged with "Prettier"

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Day 4 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today I was very busy with work and college, but I managed to study, so I see this topics today:

diff --git a/blog/tags/procedures.html b/blog/tags/procedures.html index a72d1a1d..4d5510f4 100644 --- a/blog/tags/procedures.html +++ b/blog/tags/procedures.html @@ -9,8 +9,8 @@ - - + +

2 posts tagged with "Procedures"

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Day 11 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today I continue to study about the Object Relational Database using Oracle DB to a exam that I had at afternoon.

diff --git a/blog/tags/process.html b/blog/tags/process.html index 20f572ba..439b968b 100644 --- a/blog/tags/process.html +++ b/blog/tags/process.html @@ -9,8 +9,8 @@ - - + +

One post tagged with "Process"

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Day 6 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today was a slow day for me, I can't concentrate to study, but I do some things.

diff --git a/blog/tags/programming.html b/blog/tags/programming.html index 5ba1ab8b..ab11e805 100644 --- a/blog/tags/programming.html +++ b/blog/tags/programming.html @@ -9,8 +9,8 @@ - - + +

One post tagged with "programming"

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How to Code Everyday

· 2 min read
Paulo Hernane
Paulo Hernane
Software Engineer

Code is a skill that you need to practice every day. But some days we don't are in the mood to code, but we fell anxious about it. So, I will share with you some tips that I use to code every day.

diff --git a/blog/tags/python.html b/blog/tags/python.html index 8dc87e7c..90a60696 100644 --- a/blog/tags/python.html +++ b/blog/tags/python.html @@ -9,8 +9,8 @@ - - + +

One post tagged with "Python"

View All Tags
diff --git a/blog/tags/react-native.html b/blog/tags/react-native.html index f764c2b3..e8339e3e 100644 --- a/blog/tags/react-native.html +++ b/blog/tags/react-native.html @@ -9,8 +9,8 @@ - - + +

One post tagged with "React Native"

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Day 11 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today I continue to study about the Object Relational Database using Oracle DB to a exam that I had at afternoon.

diff --git a/blog/tags/react.html b/blog/tags/react.html index 115466f5..4b087f80 100644 --- a/blog/tags/react.html +++ b/blog/tags/react.html @@ -9,8 +9,8 @@ - - + +

One post tagged with "React"

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Day 2 of 100 Days of Code

· 2 min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today was a really full day of work, I have been working to finish a project that I have been working on for a while from the company that I work for, so I didn't have much time to code, but I managed to do some things.

diff --git a/blog/tags/routine.html b/blog/tags/routine.html index 24f4202b..7f2e8491 100644 --- a/blog/tags/routine.html +++ b/blog/tags/routine.html @@ -9,8 +9,8 @@ - - + +

2 posts tagged with "Routine"

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Day 6 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today was a slow day for me, I can't concentrate to study, but I do some things.

diff --git a/blog/tags/seaborn.html b/blog/tags/seaborn.html index a47bae7c..f969537c 100644 --- a/blog/tags/seaborn.html +++ b/blog/tags/seaborn.html @@ -9,8 +9,8 @@ - - + +

One post tagged with "Seaborn"

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Day 3 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today I finished the second lab for my Data Science class, I used Pandas and Seaborn library to plot some histograms and boxplots, maybe I would write a post about it soon. You can check the notebook here.

diff --git a/blog/tags/swc.html b/blog/tags/swc.html index a3e73791..4207e963 100644 --- a/blog/tags/swc.html +++ b/blog/tags/swc.html @@ -9,8 +9,8 @@ - - + +

One post tagged with "SWC"

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Day 5 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today was nice, I study lot of things and at the end of the day I release a game!

diff --git a/blog/tags/synchronization-patterns.html b/blog/tags/synchronization-patterns.html index db108847..f573a31d 100644 --- a/blog/tags/synchronization-patterns.html +++ b/blog/tags/synchronization-patterns.html @@ -9,8 +9,8 @@ - - + +

One post tagged with "Synchronization Patterns"

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Day 1 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today I started studying Go by doing the exercises in the repository of @wagslane fcc-learn-golang-assets.

diff --git a/blog/tags/thread.html b/blog/tags/thread.html index 4dfa6541..c129b118 100644 --- a/blog/tags/thread.html +++ b/blog/tags/thread.html @@ -9,8 +9,8 @@ - - + +

One post tagged with "Thread"

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Day 6 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today was a slow day for me, I can't concentrate to study, but I do some things.

diff --git a/blog/tags/typescript.html b/blog/tags/typescript.html index adc18eb3..700a0813 100644 --- a/blog/tags/typescript.html +++ b/blog/tags/typescript.html @@ -9,8 +9,8 @@ - - + +

2 posts tagged with "Typescript"

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Day 4 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today I was very busy with work and college, but I managed to study, so I see this topics today:

diff --git a/blog/tags/v-array.html b/blog/tags/v-array.html index da1d1c04..7d455ae9 100644 --- a/blog/tags/v-array.html +++ b/blog/tags/v-array.html @@ -9,8 +9,8 @@ - - + +

2 posts tagged with "VArray"

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Day 11 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today I continue to study about the Object Relational Database using Oracle DB to a exam that I had at afternoon.

diff --git a/blog/tags/zod.html b/blog/tags/zod.html index b3b461a5..e7991502 100644 --- a/blog/tags/zod.html +++ b/blog/tags/zod.html @@ -9,8 +9,8 @@ - - + +

One post tagged with "zod"

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Day 4 of 100 Days of Code

· One min read
Paulo Hernane
Paulo Hernane
Software Engineer

Today I was very busy with work and college, but I managed to study, so I see this topics today:

diff --git a/index.html b/index.html index a8062a69..1d8badd7 100644 --- a/index.html +++ b/index.html @@ -9,8 +9,8 @@ - - + +
diff --git a/laliga/inimigos.html b/laliga/inimigos.html index 5a568aa9..1803fa29 100644 --- a/laliga/inimigos.html +++ b/laliga/inimigos.html @@ -9,8 +9,8 @@ - - + +

Inimigos dos LaLiga&Rachadores

diff --git a/my-brain/Inter-Process Communication.html b/my-brain/Inter-Process Communication.html index 4cc39a6e..e261a53f 100644 --- a/my-brain/Inter-Process Communication.html +++ b/my-brain/Inter-Process Communication.html @@ -9,11 +9,11 @@ - - + + -

Inter-Process Communication (IPC)

+

Inter-Process Communication (IPC)

All the time the processes need to communicate with each other to exchange information, like a server with a database, this process is called Inter-Process Communication.

There various methods to implements IPC, like:

Shared Memory

diff --git a/my-brain/concurrent-programming.html b/my-brain/concurrent-programming.html index 4b70c6cc..9fbba601 100644 --- a/my-brain/concurrent-programming.html +++ b/my-brain/concurrent-programming.html @@ -9,11 +9,11 @@ - - + + -

Concurrent Programming

+

Concurrent Programming

This section contains my notes take during my "Programação Concorrente" classes at Universidade Federal de Campina Grande.

Book that I used to study: The Little Book of Semaphores.

diff --git a/my-brain/concurrent-programming/basic-synchronization-patterns.html b/my-brain/concurrent-programming/basic-synchronization-patterns.html index 2f415240..312c5945 100644 --- a/my-brain/concurrent-programming/basic-synchronization-patterns.html +++ b/my-brain/concurrent-programming/basic-synchronization-patterns.html @@ -9,11 +9,11 @@ - - + + -

Basic Synchronization Patterns

+

Basic Synchronization Patterns

This are the basic synchronization patterns that can be used to solve a variety of synchronization problems.

In the examples the main function is the main thread, and the f1 and f2 are functions that can be run by threads, they run concurrently and can be run in any order.

Signalizing

diff --git a/my-brain/concurrent-programming/classical-synchronization-problems.html b/my-brain/concurrent-programming/classical-synchronization-problems.html index fe93c30a..1eb06275 100644 --- a/my-brain/concurrent-programming/classical-synchronization-problems.html +++ b/my-brain/concurrent-programming/classical-synchronization-problems.html @@ -9,11 +9,11 @@ - - + + -

Classical Synchronization Problems

+

Classical Synchronization Problems

Producer-Consumer Problem

Solving using Semaphores

# main
diff --git a/my-brain/concurrent-programming/concurrency-vs-parallelism.html b/my-brain/concurrent-programming/concurrency-vs-parallelism.html
index 604a40a0..04ae648a 100644
--- a/my-brain/concurrent-programming/concurrency-vs-parallelism.html
+++ b/my-brain/concurrent-programming/concurrency-vs-parallelism.html
@@ -9,11 +9,11 @@
 
 
 
-
-
+
+
 
 
-
Concurrency vs Parallelism

+
Concurrency vs Parallelism

 
Alt text

 
Definitions
\ No newline at end of file diff --git a/my-brain/linux.html b/my-brain/linux.html index d516a577..96ca1171 100644 --- a/my-brain/linux.html +++ b/my-brain/linux.html @@ -9,11 +9,11 @@ - - + + -

Linux

Some notes about Linux.

+

Linux

Some notes about Linux.

Resources:

  • Linux Device Drivers Development Course for Beginners
    • diff --git a/my-brain/linux/driver-development.html b/my-brain/linux/driver-development.html index 9fb7ced8..55a01db4 100644 --- a/my-brain/linux/driver-development.html +++ b/my-brain/linux/driver-development.html @@ -9,11 +9,11 @@ - - + + -

    Driver Development

    The most simple drive code had to have the functions module_init and module_exit to initialize and finalize the module. This are C macros that are defined in the linux/init.h header file.

    +

    Driver Development

    The most simple drive code had to have the functions module_init and module_exit to initialize and finalize the module. This are C macros that are defined in the linux/init.h header file.

    
 ### module_init
 
diff --git a/my-brain/linux/driver-development/make-and-makefile.html b/my-brain/linux/driver-development/make-and-makefile.html
index 3f3554e8..898d5690 100644
--- a/my-brain/linux/driver-development/make-and-makefile.html
+++ b/my-brain/linux/driver-development/make-and-makefile.html
@@ -9,11 +9,11 @@
 
 
 
-
-
+
+
 
 
-
    Make and Makefile
    Make
    
+
    Make and Makefile
    Make
    
 
    make is a automation tool that helps we to executing commands in a more organized way. It is used to compile and build large projects, but it can be used for any task that requires executing a series of commands.
    
 
    Its usefull when we have a project with multiple files and we need to compile them in a specific order. Instead of compiling each file manually, we can use make to automate the process.
    
 
    Usage
    
diff --git a/my-brain/linux/driver.html b/my-brain/linux/driver.html
index e8a1b310..3a5f7ec7 100644
--- a/my-brain/linux/driver.html
+++ b/my-brain/linux/driver.html
@@ -9,11 +9,11 @@
 
 
 
-
-
+
+
 
 
-
    Driver
    alt text
    
+
    Driver
    alt text
    
 
    A driver is a piece of software that allows the operating system to communicate with hardware devices. It acts as a translator between the hardware and the software, allowing the operating system to send commands to the hardware and receive data from it.
    
 
    There are three main types of drivers in Linux:
    
 
      
diff --git a/my-brain/linux/files.html b/my-brain/linux/files.html
index 80580a67..2e81df36 100644
--- a/my-brain/linux/files.html
+++ b/my-brain/linux/files.html
@@ -9,11 +9,11 @@
 
 
 
-
-
+
+
 
 
-
      Files
      Files are a fundamental concept in Linux and other operating systems. They are used to store data, programs, and other information on disk. In Linux, files are organized into a hierarchical directory structure, with directories containing files and other directories. This structure is similar to a tree, with the root directory at the top and subdirectories branching off from it.
      
+
      Files
      Files are a fundamental concept in Linux and other operating systems. They are used to store data, programs, and other information on disk. In Linux, files are organized into a hierarchical directory structure, with directories containing files and other directories. This structure is similar to a tree, with the root directory at the top and subdirectories branching off from it.
      
 
      Device drivers System Calls
      
 
      One of the most commons system calls that a device driver implements is File Operations.
      
 
      Linux exposes a device as a file. The common operations over a file is related to a device too.
      
diff --git a/my-brain/linux/linux-kernel.html b/my-brain/linux/linux-kernel.html
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-
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+
 
 
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      Linux Kernel
      The Linux kernel is the core of the Linux operating system. It is responsible for managing hardware resources, scheduling processes, and providing a secure environment for applications to run.
      
+
      Linux Kernel
      The Linux kernel is the core of the Linux operating system. It is responsible for managing hardware resources, scheduling processes, and providing a secure environment for applications to run.
      
 
      The kernel is a abstraction layer between the hardware and the software. It is the first program that runs when the computer is turned on.
      
 
      alt text
      
 
      The kernel has
diff --git a/my-brain/linux/system-call.html b/my-brain/linux/system-call.html
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-
      System Call
      System calls are the API interface between the user programs and the kernel. The kernel provides a set of system calls that user programs can use to request services from the kernel.
      
+
      System Call
      System calls are the API interface between the user programs and the kernel. The kernel provides a set of system calls that user programs can use to request services from the kernel.
      
 
 
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diff --git a/my-brain/machine-learning-and-data-science-course.html b/my-brain/machine-learning-and-data-science-course.html
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-
      Machine Learning and Data Science from A to Z
      Part 1 - Classification
      
+
      Machine Learning and Data Science from A to Z
      Part 1 - Classification
      
 
        
 
      • Data Pre-processing
        • 
 
      • Naive Bayes
        • 
diff --git a/my-brain/machine-learning-and-data-science-course/classification.html b/my-brain/machine-learning-and-data-science-course/classification.html
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-
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-
        Classification
          
+
          Classification
            
 
          • Pre-processing and preparation of the data for classification
            • 
 
          • Naive Bayes
            • 
 
          • Decision Trees
            • 
diff --git a/my-brain/machine-learning-and-data-science-course/classification/decision-trees.html b/my-brain/machine-learning-and-data-science-course/classification/decision-trees.html
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-
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-
            Decision trees are a popular machine learning algorithm used for classification and regression tasks. They are easy to interpret and visualize, making them a popular choice for decision-making tasks.
            
+
            Decision trees are a popular machine learning algorithm used for classification and regression tasks. They are easy to interpret and visualize, making them a popular choice for decision-making tasks.
            
 
            alt text
            
 
            Sumary
            
 
              
diff --git a/my-brain/machine-learning-and-data-science-course/classification/naive-bayes.html b/my-brain/machine-learning-and-data-science-course/classification/naive-bayes.html
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-
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-
              naive-bayes
              Naive Bayes is a classification algorithm based on Bayes' theorem. It is simple and fast, and it is often used as a baseline for comparison with other more complex algorithms.
              
+
              naive-bayes
              Naive Bayes is a classification algorithm based on Bayes' theorem. It is simple and fast, and it is often used as a baseline for comparison with other more complex algorithms.
              
 
              This use a probabilistic approach (Bayes' theorem) to classify data. It assumes that the presence of a particular feature in a class is unrelated to the presence of any other feature.
              
 
              Examples:
              
 
                
diff --git a/my-brain/machine-learning-and-data-science-course/classification/naive-bayes/how-it-works.html b/my-brain/machine-learning-and-data-science-course/classification/naive-bayes/how-it-works.html
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-
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-
                How it works
                  
+
                  How it works
                    
 
                  1. We create a probability table for each class.
                    2. 
 
                  2. We calculate the prior probabilities for each class.
                    3. 
 
                  
diff --git a/my-brain/machine-learning-and-data-science-course/computer-vision.html b/my-brain/machine-learning-and-data-science-course/computer-vision.html
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-
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+
 
 
-
                  Computer Vision
                  Computer vision is a field of artificial intelligence that focuses on enabling computers to interpret and understand the visual world. It involves the development of algorithms and techniques that allow computers to extract information from images or videos.
                  
+
                  Computer Vision
                  Computer vision is a field of artificial intelligence that focuses on enabling computers to interpret and understand the visual world. It involves the development of algorithms and techniques that allow computers to extract information from images or videos.
                  
 
                    
 
                  • Object and face detection
                    • 
 
                  • Face recognition
                    • 
diff --git a/my-brain/machine-learning-and-data-science-course/data-pre-processing.html b/my-brain/machine-learning-and-data-science-course/data-pre-processing.html
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-
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-
                    Data Pre-processing
                    Data pre-processing is a crucial step in the data analysis process. It involves cleaning, transforming, and preparing raw data into a format suitable for analysis. The quality of the data and the accuracy of the results depend on the pre-processing steps. Here are some common data pre-processing techniques:
                    
+
                    Data Pre-processing
                    Data pre-processing is a crucial step in the data analysis process. It involves cleaning, transforming, and preparing raw data into a format suitable for analysis. The quality of the data and the accuracy of the results depend on the pre-processing steps. Here are some common data pre-processing techniques:
                    
 
                      
 
                    1. Load the data: Import the data from various sources such as CSV files, databases, APIs, etc.
                      2. 
 
                    2. Handle inconsistent data: Check for missing values, duplicate records, and outliers.
                      3. 
diff --git a/my-brain/machine-learning-and-data-science-course/data-pre-processing/categorical-variables.html b/my-brain/machine-learning-and-data-science-course/data-pre-processing/categorical-variables.html
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-
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-
                      Categorical Variables
                      To use some variables that are categorical we need to transform them into numerical values. This process is known as encoding or feature encoding.
                      
+
                      Categorical Variables
                      To use some variables that are categorical we need to transform them into numerical values. This process is known as encoding or feature encoding.
                      
 
                      Label Encoding
                      
 
                      Label encoding is a technique used to convert categorical variables into numerical values. It assigns a unique integer to each category in the variable.
                      
 
                      from sklearn.preprocessing import LabelEncoder
diff --git a/my-brain/machine-learning-and-data-science-course/data-pre-processing/data-standardization.html b/my-brain/machine-learning-and-data-science-course/data-pre-processing/data-standardization.html
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-
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+
 
 
-
                      Data Standardization
                      Whem working with some algorithms, we need to standardize the data to a common scale, cause some algorithms are sensitive to the scale of the input data.
                      
+
                      Data Standardization
                      Whem working with some algorithms, we need to standardize the data to a common scale, cause some algorithms are sensitive to the scale of the input data.
                      
 
                      Standardization
                      
 
                      x = (x - mean(x)) / standard deviation(x)
                      
 
                      Where:
                      
diff --git a/my-brain/machine-learning-and-data-science-course/data-pre-processing/handle-inconsistent-data.html b/my-brain/machine-learning-and-data-science-course/data-pre-processing/handle-inconsistent-data.html
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-
-
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+
 
 
-
                      Handle Inconsistent Data
                      The best way to handle inconsistent values depends on the dataset and the problem you are trying to solve. Here are some common strategies:
                      
+
                      Handle Inconsistent Data
                      The best way to handle inconsistent values depends on the dataset and the problem you are trying to solve. Here are some common strategies:
                      
 
                        
 
                      • 
 
                        Remove: Remove the rows or columns with inconsistent values. This is the simplest approach but can lead to a loss of valuable information.
                        
diff --git a/my-brain/machine-learning-and-data-science-course/data-pre-processing/split-data.html b/my-brain/machine-learning-and-data-science-course/data-pre-processing/split-data.html
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-
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+
 
 
-
                        Split Data
                        We need to split the data in previsor variables and target variable. We will use the previsor variables to predict the target variable. The target variable is the variable we are trying to predict.
                        
+
                        Split Data
                        We need to split the data in previsor variables and target variable. We will use the previsor variables to predict the target variable. The target variable is the variable we are trying to predict.
                        
 
                        Split Data
                        
 
                        import pandas as pd
 
diff --git a/my-brain/machine-learning-and-data-science-course/data-pre-processing/variables-types.html b/my-brain/machine-learning-and-data-science-course/data-pre-processing/variables-types.html
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-
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+
+
 
 
-
                        Variables Types
                        We need to now the variables types to better use and choose the right algorithms.
                        
+
                        Variables Types
                        We need to now the variables types to better use and choose the right algorithms.
                        
 
                        Variables Types
                        
 
                        Numerical Variables
                        
 
                          
diff --git a/my-brain/machine-learning-and-data-science-course/dimensionality-reduction.html b/my-brain/machine-learning-and-data-science-course/dimensionality-reduction.html
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-
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-
                          Dimensionality Reduction
                          Feature selection X Feature extraction
                          
+
                          Dimensionality Reduction
                          Feature selection X Feature extraction
                          
 
                          Feature selection is the process of selecting a subset of the most important features from a dataset.
                          
 
                          Feature extraction is the process of creating new features from the existing features in a dataset. Dimensionality reduction techniques such as PCA and LDA are examples of feature extraction.
                          
 
                          Dimensionality Reduction is the process of reducing the number of features in a dataset by selecting a subset of the most important features or by transforming the data into a lower-dimensional space.
                          
diff --git a/my-brain/machine-learning-and-data-science-course/feature-engineering-and-selection.html b/my-brain/machine-learning-and-data-science-course/feature-engineering-and-selection.html
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-
-
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+
 
 
-
                          Feature Engineering and Selection
                          It's note true that more atributtes will make a model better.
+
                          Feature Engineering and Selection
                          It's note true that more atributtes will make a model better.
 So we need to select the best features to use in our model.
                          
 
                          Low variance
                          
 
                          Variance is a measure of how much the value is spread out (has a large range).
diff --git a/my-brain/machine-learning-and-data-science-course/model-validation.html b/my-brain/machine-learning-and-data-science-course/model-validation.html
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-
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-
                          Model Validation
                          Model validation is the process of evaluating the performance of a machine learning model. It is essential to ensure that the model generalizes well to new, unseen data. There are several techniques for model validation, including:
                          
+
                          Model Validation
                          Model validation is the process of evaluating the performance of a machine learning model. It is essential to ensure that the model generalizes well to new, unseen data. There are several techniques for model validation, including:
                          
 
                            
 
                          1. 
 
                            Train/Test Split: The dataset is divided into two parts: a training set and a test set. The model is trained on the training set and evaluated on the test set. This is the simplest form of model validation.
                            
diff --git a/my-brain/machine-learning-and-data-science-course/outliers.html b/my-brain/machine-learning-and-data-science-course/outliers.html
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-
-
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+
 
 
-
                            Outliers
                            Outliers are:
                            
+
                            Outliers
                            Outliers are:
                            
 
                              
 
                            • Abnormal values
                              • 
 
                            • non-standard values
                              • 
diff --git a/my-brain/machine-learning-and-data-science-course/resampling.html b/my-brain/machine-learning-and-data-science-course/resampling.html
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-
-
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-
                              Resampling
                              alt text
                              
+
                              Resampling
                              alt text
                              
 
                              Resampling is a technique used to address imbalanced datasets, where one class is significantly more frequent than the other. This can lead to biased models that perform poorly on the minority class. Resampling methods aim to balance the dataset by either oversampling the minority class or undersampling the majority class.
                              
 
                              Undersampling
                              
 
                                
diff --git a/my-brain/machine-learning-and-data-science-course/time-series.html b/my-brain/machine-learning-and-data-science-course/time-series.html
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-
                                Time Series
                                Time series data is a sequence of data points collected at regular intervals over time. It is used in various fields such as finance, economics, weather forecasting, and signal processing. Time series analysis involves analyzing, modeling, and forecasting the patterns in the data.
                                
+
                                Time Series
                                Time series data is a sequence of data points collected at regular intervals over time. It is used in various fields such as finance, economics, weather forecasting, and signal processing. Time series analysis involves analyzing, modeling, and forecasting the patterns in the data.
                                
 
                                import pandas as pd
 
 data = {
diff --git a/my-brain/math.html b/my-brain/math.html
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                                Math
                                This section is about math.
                                
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                                Math
                                This section is about math.
                                
 
 
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                                Probability
                                Probability is the branch of mathematics that deals with how likely an event is to occur or how likely it is that a proposition is true.
                                
+
                                Probability
                                Probability is the branch of mathematics that deals with how likely an event is to occur or how likely it is that a proposition is true.
                                
 
                                This gives us two clear avenues to pursue with learning probability:
                                
 
                                  
 
                                • Probability of future events
                                  • 
diff --git a/my-brain/math/probability/bayes-theorem.html b/my-brain/math/probability/bayes-theorem.html
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-
                                  Bayes Theorem
                                  Bayes' Theorem is a fundamental theorem in probability theory that describes the probability of an event, based on prior knowledge of conditions that might be related to the event.
                                  
+
                                  Bayes Theorem
                                  Bayes' Theorem is a fundamental theorem in probability theory that describes the probability of an event, based on prior knowledge of conditions that might be related to the event.
                                  
 
                                  P(A|B) = [ P(B|A) * P(A) ] / P(B)
                                  
 
 
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                                  System Design
                                  Contents that I want to learn about distributed systems:
                                  
+
                                  System Design
                                  Contents that I want to learn about distributed systems:
                                  
 
                                  NameTypeLink
                                  Designing Data Intensive ApplicationsBook⛓️
                                  Design Patterns for Distributed SystemsArticle⛓️
                                  How Message Queues Work in Distributed SystemsArticle⛓️
                                  System Design for Beginners CourseCourse⛓️
                                  System Design by Gaurav SenPlaylist⛓️
                                  Distributed Systems: Principles and Paradigms by TanenbaumBook⛓️
                                  Distributed System course USPCourse⛓️
                                  
 
                                  Some notes (will become a content to learn)
                                  
 
                                    
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                                    Tags
                                    
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                                    naive-bayes
                                    Naive Bayes is a classification algorithm based on Bayes' theorem. It is simple and fast, and it is often used as a baseline for comparison with other more complex algorithms.
                                    
diff --git a/my-brain/tags/clustering.html b/my-brain/tags/clustering.html
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                                    K-Means Clustering
                                    K-Means Clustering is an unsupervided machine learning model, that belongs to the class of clustering algotithms.
                                    
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                                    Computer Vision
                                    Computer vision is a field of artificial intelligence that focuses on enabling computers to interpret and understand the visual world. It involves the development of algorithms and techniques that allow computers to extract information from images or videos.
                                    
diff --git a/my-brain/tags/conceptual-data-model.html b/my-brain/tags/conceptual-data-model.html
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diff --git a/my-brain/tags/concurrent-programming.html b/my-brain/tags/concurrent-programming.html
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                                    Semaphore
                                    Before understand what is a semaphore, we need to understand some concepts:
                                    
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                                    One doc tagged with "Correlation"
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diff --git a/my-brain/tags/data-model.html b/my-brain/tags/data-model.html
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diff --git a/my-brain/tags/data-preprocessing.html b/my-brain/tags/data-preprocessing.html
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                                    3 docs tagged with "data-preprocessing"
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                                    Time Series
                                    Time series data is a sequence of data points collected at regular intervals over time. It is used in various fields such as finance, economics, weather forecasting, and signal processing. Time series analysis involves analyzing, modeling, and forecasting the patterns in the data.
                                    
diff --git a/my-brain/tags/data-science.html b/my-brain/tags/data-science.html
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                                    7 docs tagged with "Data Science"
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                                    decision-tree
                                    Decision trees are a popular machine learning algorithm used for classification and regression tasks. They are easy to interpret and visualize, making them a popular choice for decision-making tasks.
                                    Histogram
                                    Histogram is a graphical used to visualize the distribution of a numerical variable. It is a type of bar chart that shows the frequency of each value.
                                    How it works
                                    1. We create a probability table for each class.
                                    K-Means Clustering
                                    K-Means Clustering is an unsupervided machine learning model, that belongs to the class of clustering algotithms.
                                    Model Validation
                                    Model validation is the process of evaluating the performance of a machine learning model. It is essential to ensure that the model generalizes well to new, unseen data. There are several techniques for model validation, including:
                                    
diff --git a/my-brain/tags/database-administrator.html b/my-brain/tags/database-administrator.html
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diff --git a/my-brain/tags/database-management-system.html b/my-brain/tags/database-management-system.html
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                                    One doc tagged with "Database Management System"
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diff --git a/my-brain/tags/database.html b/my-brain/tags/database.html
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                                    One doc tagged with "database"
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diff --git a/my-brain/tags/databases.html b/my-brain/tags/databases.html
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                                    One doc tagged with "Databases"
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diff --git a/my-brain/tags/dba.html b/my-brain/tags/dba.html
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                                    One doc tagged with "DBA"
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diff --git a/my-brain/tags/dbms.html b/my-brain/tags/dbms.html
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                                    One doc tagged with "DBMS"
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diff --git a/my-brain/tags/decision-trees.html b/my-brain/tags/decision-trees.html
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                                    One doc tagged with "decision trees"
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                                    decision-tree
                                    Decision trees are a popular machine learning algorithm used for classification and regression tasks. They are easy to interpret and visualize, making them a popular choice for decision-making tasks.
                                    
diff --git a/my-brain/tags/deep-learning.html b/my-brain/tags/deep-learning.html
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                                    One doc tagged with "deep-learning"
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                                    Computer Vision
                                    Computer vision is a field of artificial intelligence that focuses on enabling computers to interpret and understand the visual world. It involves the development of algorithms and techniques that allow computers to extract information from images or videos.
                                    
diff --git a/my-brain/tags/design-patterns.html b/my-brain/tags/design-patterns.html
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                                    One doc tagged with "Design Patterns"
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                                    System Design
                                    Contents that I want to learn about distributed systems:
                                    
diff --git a/my-brain/tags/development.html b/my-brain/tags/development.html
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                                    One doc tagged with "development"
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                                    Driver Development
                                    The most simple drive code had to have the functions moduleinit and moduleexit to initialize and finalize the module. This are C macros that are defined in the linux/init.h header file.
                                    
diff --git a/my-brain/tags/dimensionality-reduction.html b/my-brain/tags/dimensionality-reduction.html
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                                    One doc tagged with "dimensionality-reduction"
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diff --git a/my-brain/tags/disk-storage.html b/my-brain/tags/disk-storage.html
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                                    One doc tagged with "disk-storage"
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diff --git a/my-brain/tags/distributed-systems.html b/my-brain/tags/distributed-systems.html
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                                    2 docs tagged with "Distributed Systems"
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                                    inter-process-communication
                                    All the time the processes need to communicate with each other to exchange information, like a server with a database, this process is called Inter-Process Communication.
                                    System Design
                                    Contents that I want to learn about distributed systems:
                                    
diff --git a/my-brain/tags/driver.html b/my-brain/tags/driver.html
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                                    2 docs tagged with "driver"
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                                    Driver Development
                                    The most simple drive code had to have the functions moduleinit and moduleexit to initialize and finalize the module. This are C macros that are defined in the linux/init.h header file.
                                    
diff --git a/my-brain/tags/elbow-method.html b/my-brain/tags/elbow-method.html
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                                    One doc tagged with "Elbow Method"
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                                    K-Means Clustering
                                    K-Means Clustering is an unsupervided machine learning model, that belongs to the class of clustering algotithms.
                                    
diff --git a/my-brain/tags/em-algorithm.html b/my-brain/tags/em-algorithm.html
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                                    One doc tagged with "EM Algorithm"
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                                    K-Means Clustering
                                    K-Means Clustering is an unsupervided machine learning model, that belongs to the class of clustering algotithms.
                                    
diff --git a/my-brain/tags/entity-relationship-model.html b/my-brain/tags/entity-relationship-model.html
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                                    One doc tagged with "Entity-Relationship Model"
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diff --git a/my-brain/tags/exclusion.html b/my-brain/tags/exclusion.html
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                                    2 docs tagged with "Exclusion"
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                                    Semaphore
                                    Before understand what is a semaphore, we need to understand some concepts:
                                    
diff --git a/my-brain/tags/expectation-maximization.html b/my-brain/tags/expectation-maximization.html
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                                    One doc tagged with "Expectation–Maximization"
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                                    K-Means Clustering
                                    K-Means Clustering is an unsupervided machine learning model, that belongs to the class of clustering algotithms.
                                    
diff --git a/my-brain/tags/feature-engineering.html b/my-brain/tags/feature-engineering.html
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                                    One doc tagged with "feature-engineering"
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diff --git a/my-brain/tags/feature-extraction.html b/my-brain/tags/feature-extraction.html
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diff --git a/my-brain/tags/feature-selection.html b/my-brain/tags/feature-selection.html
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                                    2 docs tagged with "feature-selection"
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diff --git a/my-brain/tags/file-structures.html b/my-brain/tags/file-structures.html
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                                    One doc tagged with "file-structures"
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diff --git a/my-brain/tags/files.html b/my-brain/tags/files.html
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                                    One doc tagged with "files"
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                                    Files
                                    Files are a fundamental concept in Linux and other operating systems. They are used to store data, programs, and other information on disk. In Linux, files are organized into a hierarchical directory structure, with directories containing files and other directories. This structure is similar to a tree, with the root directory at the top and subdirectories branching off from it.
                                    
diff --git a/my-brain/tags/forecasting.html b/my-brain/tags/forecasting.html
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                                    One doc tagged with "forecasting"
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                                    Time Series
                                    Time series data is a sequence of data points collected at regular intervals over time. It is used in various fields such as finance, economics, weather forecasting, and signal processing. Time series analysis involves analyzing, modeling, and forecasting the patterns in the data.
                                    
diff --git a/my-brain/tags/hashing.html b/my-brain/tags/hashing.html
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                                    One doc tagged with "hashing"
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diff --git a/my-brain/tags/histogram.html b/my-brain/tags/histogram.html
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                                    One doc tagged with "Histogram"
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                                    Histogram
                                    Histogram is a graphical used to visualize the distribution of a numerical variable. It is a type of bar chart that shows the frequency of each value.
                                    
diff --git a/my-brain/tags/image-processing.html b/my-brain/tags/image-processing.html
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                                    One doc tagged with "image-processing"
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                                    Computer Vision
                                    Computer vision is a field of artificial intelligence that focuses on enabling computers to interpret and understand the visual world. It involves the development of algorithms and techniques that allow computers to extract information from images or videos.
                                    
diff --git a/my-brain/tags/imbalanced-data.html b/my-brain/tags/imbalanced-data.html
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diff --git a/my-brain/tags/inter-process-communication.html b/my-brain/tags/inter-process-communication.html
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                                    inter-process-communication
                                    All the time the processes need to communicate with each other to exchange information, like a server with a database, this process is called Inter-Process Communication.
                                    
diff --git a/my-brain/tags/ipc.html b/my-brain/tags/ipc.html
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                                    One doc tagged with "IPC"
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                                    inter-process-communication
                                    All the time the processes need to communicate with each other to exchange information, like a server with a database, this process is called Inter-Process Communication.
                                    
diff --git a/my-brain/tags/k-means.html b/my-brain/tags/k-means.html
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                                    K-Means Clustering
                                    K-Means Clustering is an unsupervided machine learning model, that belongs to the class of clustering algotithms.
                                    
diff --git a/my-brain/tags/linux.html b/my-brain/tags/linux.html
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                                    4 docs tagged with "linux"
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                                    Driver Development
                                    The most simple drive code had to have the functions moduleinit and moduleexit to initialize and finalize the module. This are C macros that are defined in the linux/init.h header file.
                                    Files
                                    Files are a fundamental concept in Linux and other operating systems. They are used to store data, programs, and other information on disk. In Linux, files are organized into a hierarchical directory structure, with directories containing files and other directories. This structure is similar to a tree, with the root directory at the top and subdirectories branching off from it.
                                    System Call
                                    System calls are the API interface between the user programs and the kernel. The kernel provides a set of system calls that user programs can use to request services from the kernel.
                                    
diff --git a/my-brain/tags/logic-data-model.html b/my-brain/tags/logic-data-model.html
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diff --git a/my-brain/tags/machine-learning.html b/my-brain/tags/machine-learning.html
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                                    9 docs tagged with "Machine Learning"
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                                    Computer Vision
                                    Computer vision is a field of artificial intelligence that focuses on enabling computers to interpret and understand the visual world. It involves the development of algorithms and techniques that allow computers to extract information from images or videos.
                                    decision-tree
                                    Decision trees are a popular machine learning algorithm used for classification and regression tasks. They are easy to interpret and visualize, making them a popular choice for decision-making tasks.
                                    How it works
                                    1. We create a probability table for each class.
                                    K-Means Clustering
                                    K-Means Clustering is an unsupervided machine learning model, that belongs to the class of clustering algotithms.
                                    Model Validation
                                    Model validation is the process of evaluating the performance of a machine learning model. It is essential to ensure that the model generalizes well to new, unseen data. There are several techniques for model validation, including:
                                    naive-bayes
                                    Naive Bayes is a classification algorithm based on Bayes' theorem. It is simple and fast, and it is often used as a baseline for comparison with other more complex algorithms.
                                    
diff --git a/my-brain/tags/make.html b/my-brain/tags/make.html
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diff --git a/my-brain/tags/makefile.html b/my-brain/tags/makefile.html
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diff --git a/my-brain/tags/math.html b/my-brain/tags/math.html
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                                    Math
                                    This section is about math.
                                    
diff --git a/my-brain/tags/mer.html b/my-brain/tags/mer.html
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diff --git a/my-brain/tags/model-validation.html b/my-brain/tags/model-validation.html
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                                    Model Validation
                                    Model validation is the process of evaluating the performance of a machine learning model. It is essential to ensure that the model generalizes well to new, unseen data. There are several techniques for model validation, including:
                                    
diff --git a/my-brain/tags/multiplex.html b/my-brain/tags/multiplex.html
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diff --git a/my-brain/tags/mutex.html b/my-brain/tags/mutex.html
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                                    Semaphore
                                    Before understand what is a semaphore, we need to understand some concepts:
                                    
diff --git a/my-brain/tags/naive-bayes.html b/my-brain/tags/naive-bayes.html
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                                    How it works
                                    1. We create a probability table for each class.
                                    
diff --git a/my-brain/tags/object-oriented-model.html b/my-brain/tags/object-oriented-model.html
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diff --git a/my-brain/tags/outliers.html b/my-brain/tags/outliers.html
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diff --git a/my-brain/tags/parallelism.html b/my-brain/tags/parallelism.html
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diff --git a/my-brain/tags/physical-data-model.html b/my-brain/tags/physical-data-model.html
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diff --git a/my-brain/tags/process.html b/my-brain/tags/process.html
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                                    K-Means Clustering
                                    K-Means Clustering is an unsupervided machine learning model, that belongs to the class of clustering algotithms.
                                    
diff --git a/my-brain/tags/race-condition.html b/my-brain/tags/race-condition.html
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                                    Semaphore
                                    Before understand what is a semaphore, we need to understand some concepts:
                                    
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diff --git a/my-brain/tags/rendezvous.html b/my-brain/tags/rendezvous.html
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                                    2 docs tagged with "Rendezvous"
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                                    Semaphore
                                    Before understand what is a semaphore, we need to understand some concepts:
                                    
diff --git a/my-brain/tags/resampling.html b/my-brain/tags/resampling.html
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diff --git a/my-brain/tags/reusable-barrier.html b/my-brain/tags/reusable-barrier.html
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diff --git a/my-brain/tags/routine.html b/my-brain/tags/routine.html
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diff --git a/my-brain/tags/sampling.html b/my-brain/tags/sampling.html
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diff --git a/my-brain/tags/scikit-learn.html b/my-brain/tags/scikit-learn.html
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                                    One doc tagged with "Scikit-Learn"
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                                    K-Means Clustering
                                    K-Means Clustering is an unsupervided machine learning model, that belongs to the class of clustering algotithms.
                                    
diff --git a/my-brain/tags/seaborn.html b/my-brain/tags/seaborn.html
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                                    Histogram
                                    Histogram is a graphical used to visualize the distribution of a numerical variable. It is a type of bar chart that shows the frequency of each value.
                                    
diff --git a/my-brain/tags/semaphore.html b/my-brain/tags/semaphore.html
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                                    Semaphore
                                    Before understand what is a semaphore, we need to understand some concepts:
                                    
diff --git a/my-brain/tags/signalizing.html b/my-brain/tags/signalizing.html
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diff --git a/my-brain/tags/silhouette-analysis.html b/my-brain/tags/silhouette-analysis.html
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                                    K-Means Clustering
                                    K-Means Clustering is an unsupervided machine learning model, that belongs to the class of clustering algotithms.
                                    
diff --git a/my-brain/tags/sqlite.html b/my-brain/tags/sqlite.html
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diff --git a/my-brain/tags/statistics.html b/my-brain/tags/statistics.html
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                                    Histogram
                                    Histogram is a graphical used to visualize the distribution of a numerical variable. It is a type of bar chart that shows the frequency of each value.
                                    
diff --git a/my-brain/tags/synchronization-patterns.html b/my-brain/tags/synchronization-patterns.html
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                                    System Call
                                    System calls are the API interface between the user programs and the kernel. The kernel provides a set of system calls that user programs can use to request services from the kernel.
                                    
diff --git a/my-brain/tags/system-design.html b/my-brain/tags/system-design.html
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                                    System Design
                                    Contents that I want to learn about distributed systems:
                                    
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diff --git a/my-brain/tags/time-series.html b/my-brain/tags/time-series.html
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                                    Time Series
                                    Time series data is a sequence of data points collected at regular intervals over time. It is used in various fields such as finance, economics, weather forecasting, and signal processing. Time series analysis involves analyzing, modeling, and forecasting the patterns in the data.
                                    
diff --git a/my-brain/tags/uml.html b/my-brain/tags/uml.html
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diff --git a/my-brain/tags/unified-modeling-language.html b/my-brain/tags/unified-modeling-language.html
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                                    K-Means Clustering
                                    K-Means Clustering is an unsupervided machine learning model, that belongs to the class of clustering algotithms.
                                    
diff --git a/my-brain/tags/xml-model.html b/my-brain/tags/xml-model.html
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diff --git a/my-brain/what-i-am-learning.html b/my-brain/what-i-am-learning.html
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                                    What I am learning
                                    This section contains the info about what I am learning.
                                    
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                                    What I am learning
                                    This section contains the info about what I am learning.
                                    
 
                                    SubjectDescriptionStatus⛓️
                                    Computer ScienceThis is my Graduation course.In ProgressComputação UFCG
                                    EnglishIn ProgressTimes Idiomas
                                    
 
 
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                                    Stack
                                    React
                                    Node
                                    MongoDB
                                    Projects
                                    Projeto 1
                                    Projeto 2
                                    
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