Syllabus
https://github.com/ogut77/DataScience/blob/main/DataScienceSpring2023.pdf
Python Programming Basics
[]https://colab.research.google.com/github/ogut77/DataScience/blob/main/PythonProgramming.ipynb ]
Python Tutorial Version 2
[]https://colab.research.google.com/github/ogut77/DataScience/blob/main/PythonTutorialV2.ipynb ]
Python Tutorial Version 3
[]https://colab.research.google.com/github/ogut77/DataScience/blob/main/PythonTutorialV3.ipynb ]
Homework 1
[]https://colab.research.google.com/github/ogut77/DataScience/blob/main/Homework1.ipynb ]
Data Processing 1
[]https://colab.research.google.com/github/ogut77/DataScience/blob/main/DataProcessing1.ipynb ]
Data Processing 2
[]https://colab.research.google.com/github/ogut77/DataScience/blob/main/DataProcessing2.ipynb ]
Data Processing 2 Answer
[]https://colab.research.google.com/github/ogut77/DataScience/blob/main/DataProcessing2Ans.ipynb ]
Homework 2
[]https://colab.research.google.com/github/ogut77/DataScience/blob/main/Homework2.ipynb ]
Linear Regression and Regulization Techniques (Lasso, Ridge, Elastic Net)
[]https://colab.research.google.com/github/ogut77/DataScience/blob/main/LR.ipynb ]
Linear Regression- Estimation
[]https://colab.research.google.com/github/ogut77/DataScience/blob/main/LREst.ipynb ]
Decision Trees- Random Forest- Classification
[]https://colab.research.google.com/github/ogut77/DataScience/blob/main/Loan.ipynb ]
Decision Trees- Random Forest- Regression
[]https://colab.research.google.com/github/ogut77/DataScience/blob/main/RfHousing.ipynb ]
Homework 3
[]https://colab.research.google.com/github/ogut77/DataScience/blob/main/Homework3.ipynb ]
Classification Metrics
[]https://colab.research.google.com/github/ogut77/DataScience/blob/main/ClassificationMetrics.ipynb ]
Boosting- Random Forest-Decision Trees- Classification
[] https://colab.research.google.com/github/ogut77/DataScience/blob/main/BostingRFDTClassifier.ipynb
Boosting- Random Forest-Decision Trees- Regression
[] https://colab.research.google.com/github/ogut77/DataScience/blob/main/BoostingRFDTRegressor.ipynb
Homework 4
[]https://colab.research.google.com/github/ogut77/DataScience/blob/main/Homework4-2023.ipynb
Cross Validation
[]https://colab.research.google.com/github/ogut77/DataScience/blob/main/CrossValidation.ipynb ]
Hyperparameter Optimization Techniques and Libraries-Boosting Classifiers- XGBoost, Light GBM, CatBoost, GradientBoosting
[]https://colab.research.google.com/github/ogut77/DataScience/blob/main/BoostingClassifiers.ipynb ]
Hyperparameter Optimization Techniques and Libraries-Boosting Regression- XGBoost, Light GBM, CatBoost, GradientBoosting
[]https://colab.research.google.com/github/ogut77/DataScience/blob/main/BoostingRegression.ipynb ]
Homework 5
[]https://colab.research.google.com/github/ogut77/DataScience/blob/main/Homework5.ipynb ]
Other Classification Methods( Logistic Regression-kNN-Naive Bayes- Suppor Vector Machine ) and Boosting Classifier
[] https://colab.research.google.com/github/ogut77/DataScience/blob/main/LR%2BkNN%2BNB%2BSVM.ipynb
Suppor Vector Regression -Linear Regression- Boosting
[] https://colab.research.google.com/github/ogut77/DataScience/blob/main/SVMLRXG.ipynb
AutoML Example- Auto Gluon
[] https://colab.research.google.com/github/ogut77/DataScience/blob/main/AutoGluon.ipynb
PCA-1
[] https://colab.research.google.com/github/ogut77/DataScience/blob/main/PCA1.ipynb
PCA-2
[] https://colab.research.google.com/github/ogut77/DataScience/blob/main/PCA2.ipynb
Homework 6
[]https://colab.research.google.com/github/ogut77/DataScience/blob/main/Homework6.ipynb ]
Homework 7
[]https://colab.research.google.com/github/ogut77/DataScience/blob/main/Homework7a.ipynb ]
Cluster-1
[]https://colab.research.google.com/github/ogut77/DataScience/blob/main/ClAuto.ipynb ]
Cluster-2
[]https://colab.research.google.com/github/ogut77/DataScience/blob/main/ClShopping.ipynb ]
Cluster-3
[]https://colab.research.google.com/github/ogut77/DataScience/blob/main/kmeansIris.ipynb ]
Cluster-4
https://pyquantnews.com/build-state-of-the-art-portfolios-machine-learning/
[] https://github.com/ogut77/DataScience/blob/main/ClusterPortfolio.ipynb)]
Stationarity Test
[]https://colab.research.google.com/github/ogut77/DataScience/blob/main/Stationary.ipynb ]
Moving Averages- Exponential Smoothings
[]https://colab.research.google.com/github/ogut77/DataScience/blob/main/Copy_of_HW.ipynb ]
ARIMA
[]https://colab.research.google.com/github/ogut77/DataScience/blob/main/Arima1.ipynb ]
SARIMA
[]https://colab.research.google.com/github/ogut77/DataScience/blob/main/SARIMA.ipynb ]
Holt Winters +TBATS -MSTL
[]https://colab.research.google.com/github/ogut77/DataScience/blob/main/Store.ipynb ]
ETS -2
[]https://colab.research.google.com/github/ogut77/DataScience/blob/main/Champagne2.ipynb ]
SARIMA+HW+ETS+TBATS
]https://colab.research.google.com/github/ogut77/DataScience/blob/main/TS-Sample.ipynb ]
Homework 8
[]https://colab.research.google.com/github/ogut77/DataScience/blob/main/Homework8.ipynb ]
Electricity Load Forecast
[]https://colab.research.google.com/github/ogut77/DataScience/blob/main/ElectricityLoadForecasting.ipynb ]
Review Final
https://github.com/ogut77/DataScience/blob/main/ReviewFinal.doc
Additional Resources:
Python Tutorial https://www.freecodecamp.org/news/python-code-examples-simple-python-program-example/
R for Forecasting https://otexts.com/fpp3/ https://github.com/ogut77/DataScience/blob/main/RforForecasting.ipynb
Pearson VS Spearman
Bias Variance Tradeoff
https://mem.ai/p/F3YoW84xKC8D5k3OPXem
https://ml.berkeley.edu/blog/posts/crash-course/part-4/
Decision Tree and Ensemble Methods
https://ml.berkeley.edu/blog/posts/crash-course/part-5/
Logistic Regression https://twitter.com/mdancho84/status/1753098317116981265/
AutoGluon https://www.kaggle.com/competitions/playground-series-s4e1/discussion/472496#2631487
Customer Life Time Value
https://analyticsindiamag.com/a-hands-on-tutorial-on-customer-lifetime-value-cltv-prediction/
Code for CLTV
https://colab.research.google.com/github/ogut77/DataScience/blob/main/CLTV.ipynb
SARIMAX Example-New York Taxi Demand https://towardsdatascience.com/newyork-taxi-demand-forecasting-with-sarimax-using-weather-data-d46c041f3f9c
Naive Bayes for Text Classification https://curiousily.com/posts/movie-review-sentiment-analysis-with-naive-bayes/
Algortihm Behing XGBoost https://towardsdatascience.com/all-you-need-to-know-about-gradient-boosting-algorithm-part-1-regression-2520a34a502
M6 Financial Forecasting Competition https://m6competition.com/
Sample Student Projects https://www.galitshmueli.com/student-projects
Kaggle Winner Solution https://www.kaggle.com/code/sudalairajkumar/winning-solutions-of-kaggle-competitions/notebook
Comparison of ML Algorithm : Boosting Technqiues ranks first top 3 rank
https://mljar.com/machine-learning/compare-ml-algorithms/
Exponentional Smoothing in R
https://afit-r.github.io/ts_exp_smoothing
Forecasting Using R-Eindoven-Slides
https://robjhyndman.com/seminars/eindhoven/
30 days of Python https://github.com/Asabeneh/30-Days-Of-Python
Pickle [Open In Colab]https://colab.research.google.com/github/ogut77/DataScience/blob/main/Pickle.ipynb ]
AutoArima and AutoETS https://colab.research.google.com/github/nixtla/statsforecast/blob/main/nbs/examples/Getting_Started_with_Auto_Arima_and_ETS.ipynb#scrollTo=nRySBmMskIps
[]https://github.com/ogut77/DataScience/blob/main/Getting_Started_with_Auto_Arima_and_ETS.ipynb]
Comparision of Clustering Algorithm https://github.com/ogut77/DataScience/blob/main/ClusteringAlgo.jpg
Cross Validation https://www.kaggle.com/code/satishgunjal/tutorial-k-fold-cross-validation
Neural Network Classifirer https://michael-fuchs-python.netlify.app/2021/02/03/nn-multi-layer-perceptron-classifier-mlpclassifier/