Week3(Classification)

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.ipynb_checkpoints

3.1-Classification.pptx

3.1-Classification.pptx

3.2-KNearestNeighbours.pptx

3.2-KNearestNeighbours.pptx

3.3-Evaluation metrics in classification.pptx

3.3-Evaluation metrics in classification.pptx

3.4-Decision trees.pptx

3.4-Decision trees.pptx

3.5-Building Decision Trees.pptx

3.5-Building Decision Trees.pptx

3.6-LogisticRegression.pptx

3.6-LogisticRegression.pptx

3.7-Linear VS Logistic Regression.pptx

3.7-Linear VS Logistic Regression.pptx

3.8-Logistic regression training.pptx

3.8-Logistic regression training.pptx

3.9-Support Vector Machine.pptx

3.9-Support Vector Machine.pptx

cell_samples.csv

cell_samples.csv

ChurnData.csv

drug200.csv

drugtree.png

ML0101EN-Clas-Decision-Trees-drug-py-v1.ipynb

ML0101EN-Clas-Decision-Trees-drug-py-v1.ipynb

ML0101EN-Clas-K-Nearest-neighbors-CustCat-py-v1.ipynb

ML0101EN-Clas-K-Nearest-neighbors-CustCat-py-v1.ipynb

ML0101EN-Clas-Logistic-Regression-churn-py-v1.ipynb

ML0101EN-Clas-Logistic-Regression-churn-py-v1.ipynb

ML0101EN-Clas-SVM-cancer-py-v1.ipynb

ML0101EN-Clas-SVM-cancer-py-v1.ipynb

teleCust1000t.csv

teleCust1000t.csv

Test.png

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