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Repository files navigation

Syllabus

https://github.com/ogut77/DataScience/blob/main/DataScienceSpring2023.pdf

Python Programming Basics

[Open In Colab]https://colab.research.google.com/github/ogut77/DataScience/blob/main/PythonProgramming.ipynb ]

Python Tutorial Version 2

[Open In Colab]https://colab.research.google.com/github/ogut77/DataScience/blob/main/PythonTutorialV2.ipynb ]

Python Tutorial Version 3

[Open In Colab]https://colab.research.google.com/github/ogut77/DataScience/blob/main/PythonTutorialV3.ipynb ]

Homework 1

[Open In Colab]https://colab.research.google.com/github/ogut77/DataScience/blob/main/Homework1.ipynb ]

Data Processing 1

[Open In Colab]https://colab.research.google.com/github/ogut77/DataScience/blob/main/DataProcessing1.ipynb ]

Data Processing 2

[Open In Colab]https://colab.research.google.com/github/ogut77/DataScience/blob/main/DataProcessing2.ipynb ]

Data Processing 2 Answer

[Open In Colab]https://colab.research.google.com/github/ogut77/DataScience/blob/main/DataProcessing2Ans.ipynb ]

Homework 2

[Open In Colab]https://colab.research.google.com/github/ogut77/DataScience/blob/main/Homework2.ipynb ]

Linear Regression and Regulization Techniques (Lasso, Ridge, Elastic Net)

[Open In Colab]https://colab.research.google.com/github/ogut77/DataScience/blob/main/LR.ipynb ]

Linear Regression- Estimation

[Open In Colab]https://colab.research.google.com/github/ogut77/DataScience/blob/main/LREst.ipynb ]

Decision Trees- Random Forest- Classification

[Open In Colab]https://colab.research.google.com/github/ogut77/DataScience/blob/main/Loan.ipynb ]

Decision Trees- Random Forest- Regression

[Open In Colab]https://colab.research.google.com/github/ogut77/DataScience/blob/main/RfHousing.ipynb ]

Homework 3

[Open In Colab]https://colab.research.google.com/github/ogut77/DataScience/blob/main/Homework3.ipynb ]

Classification Metrics

[Open In Colab]https://colab.research.google.com/github/ogut77/DataScience/blob/main/ClassificationMetrics.ipynb ]

Boosting- Random Forest-Decision Trees- Classification

[Open In Colab] https://colab.research.google.com/github/ogut77/DataScience/blob/main/BostingRFDTClassifier.ipynb

Boosting- Random Forest-Decision Trees- Regression

[Open In Colab] https://colab.research.google.com/github/ogut77/DataScience/blob/main/BoostingRFDTRegressor.ipynb

Homework 4

[Open In Colab]https://colab.research.google.com/github/ogut77/DataScience/blob/main/Homework4-2023.ipynb

Cross Validation

[Open In Colab]https://colab.research.google.com/github/ogut77/DataScience/blob/main/CrossValidation.ipynb ]

Hyperparameter Optimization Techniques and Libraries-Boosting Classifiers- XGBoost, Light GBM, CatBoost, GradientBoosting

[Open In Colab]https://colab.research.google.com/github/ogut77/DataScience/blob/main/BoostingClassifiers.ipynb ]

Hyperparameter Optimization Techniques and Libraries-Boosting Regression- XGBoost, Light GBM, CatBoost, GradientBoosting

[Open In Colab]https://colab.research.google.com/github/ogut77/DataScience/blob/main/BoostingRegression.ipynb ]

Homework 5

[Open In Colab]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

[Open In Colab] https://colab.research.google.com/github/ogut77/DataScience/blob/main/LR%2BkNN%2BNB%2BSVM.ipynb

Suppor Vector Regression -Linear Regression- Boosting

[Open In Colab] https://colab.research.google.com/github/ogut77/DataScience/blob/main/SVMLRXG.ipynb

AutoML Example- Auto Gluon

[Open In Colab] https://colab.research.google.com/github/ogut77/DataScience/blob/main/AutoGluon.ipynb

PCA-1

[Open In Colab] https://colab.research.google.com/github/ogut77/DataScience/blob/main/PCA1.ipynb

PCA-2

[Open In Colab] https://colab.research.google.com/github/ogut77/DataScience/blob/main/PCA2.ipynb

Homework 6

[Open In Colab]https://colab.research.google.com/github/ogut77/DataScience/blob/main/Homework6.ipynb ]

Homework 7

[Open In Colab]https://colab.research.google.com/github/ogut77/DataScience/blob/main/Homework7a.ipynb ]

Cluster-1

[Open In Colab]https://colab.research.google.com/github/ogut77/DataScience/blob/main/ClAuto.ipynb ]

Cluster-2

[Open In Colab]https://colab.research.google.com/github/ogut77/DataScience/blob/main/ClShopping.ipynb ]

Cluster-3

[Open In Colab]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/

[Open In Colab] https://github.com/ogut77/DataScience/blob/main/ClusterPortfolio.ipynb)]

Stationarity Test

[Open In Colab]https://colab.research.google.com/github/ogut77/DataScience/blob/main/Stationary.ipynb ]

Moving Averages- Exponential Smoothings

[Open In Colab]https://colab.research.google.com/github/ogut77/DataScience/blob/main/Copy_of_HW.ipynb ]

ARIMA

[Open In Colab]https://colab.research.google.com/github/ogut77/DataScience/blob/main/Arima1.ipynb ]

SARIMA

[Open In Colab]https://colab.research.google.com/github/ogut77/DataScience/blob/main/SARIMA.ipynb ]

Holt Winters +TBATS -MSTL

[Open In Colab]https://colab.research.google.com/github/ogut77/DataScience/blob/main/Store.ipynb ]

ETS -2

[Open In Colab]https://colab.research.google.com/github/ogut77/DataScience/blob/main/Champagne2.ipynb ]

SARIMA+HW+ETS+TBATS

Open In Colab]https://colab.research.google.com/github/ogut77/DataScience/blob/main/TS-Sample.ipynb ]

Homework 8

[Open In Colab]https://colab.research.google.com/github/ogut77/DataScience/blob/main/Homework8.ipynb ]

Electricity Load Forecast

[Open In Colab]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

https://cmdlinetips.com/2019/08/how-to-compute-pearson-and-spearman-correlation-in-python/#:~:text=Pearson%20correlation%20assumes%20that%20the,a%20non%2Dparametric%20correlation%20measure.

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

[Open In Colab]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/

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