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ChurnData.csv
ChurnData.csv
 
 
Cust_Segmentation.csv
Cust_Segmentation.csv
 
 
FuelConsumption.csv
FuelConsumption.csv
 
 
ML0101EN-Clas-Decision-Trees-drug.ipynb
ML0101EN-Clas-Decision-Trees-drug.ipynb
 
 
ML0101EN-Clas-K-Nearest-neighbors-CustCat.ipynb
ML0101EN-Clas-K-Nearest-neighbors-CustCat.ipynb
 
 
ML0101EN-Clas-Logistic-Reg-churn.ipynb
ML0101EN-Clas-Logistic-Reg-churn.ipynb
 
 
ML0101EN-Clas-SVM-cancer.ipynb
ML0101EN-Clas-SVM-cancer.ipynb
 
 
ML0101EN-Clus-DBSCN-weather.ipynb
ML0101EN-Clus-DBSCN-weather.ipynb
 
 
ML0101EN-Clus-Hierarchical-Cars.ipynb
ML0101EN-Clus-Hierarchical-Cars.ipynb
 
 
ML0101EN-Clus-K-Means-Customer-Seg.ipynb
ML0101EN-Clus-K-Means-Customer-Seg.ipynb
 
 
ML0101EN-RecSys-Collaborative-Filtering-movies.ipynb
ML0101EN-RecSys-Collaborative-Filtering-movies.ipynb
 
 
ML0101EN-RecSys-Content-Based-movies.ipynb
ML0101EN-RecSys-Content-Based-movies.ipynb
 
 
ML0101EN-Reg-Mulitple-Linear-Regression-Co2.ipynb
ML0101EN-Reg-Mulitple-Linear-Regression-Co2.ipynb
 
 
ML0101EN-Reg-NoneLinearRegression.ipynb
ML0101EN-Reg-NoneLinearRegression.ipynb
 
 
ML0101EN-Reg-Polynomial-Regression-Co2.ipynb
ML0101EN-Reg-Polynomial-Regression-Co2.ipynb
 
 
ML0101EN-Reg-Simple-Linear-Regression-Co2.ipynb
ML0101EN-Reg-Simple-Linear-Regression-Co2.ipynb
 
 
README.md
README.md
 
 
cars_clus.csv
cars_clus.csv
 
 
cell_samples.csv
cell_samples.csv
 
 
china_gdp.csv
china_gdp.csv
 
 
drug200.csv
drug200.csv
 
 
drugtree.png
drugtree.png
 
 
movies.csv
movies.csv
 
 
ratings_sample.csv
ratings_sample.csv
 
 
teleCust1000t.csv
teleCust1000t.csv
 
 
weather-stations20140101-20141231.csv
weather-stations20140101-20141231.csv
 
 

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machine_learning_with_python_jadi

Note: github does not accept files larger than 100MB. So I truncated the ratings.csv to only 3.9M rows. For the original file, please use the link in the notebook to download the dataset.

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The notebooks we use on ML course

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