learning-ml

0.1.AmznPreProp folder contains code for pre-processing text data.

Rest of the folders contain different types of ML algorithms using ROC AUC performance metric.

Each iPython notebook has a comparision table at the end for different models.

Name		Name	Last commit message	Last commit date
Latest commit History 76 Commits
0.1.AmznPreProp		0.1.AmznPreProp
1.assign_haberman_eda		1.assign_haberman_eda
10.Clustering_AmazonFineFoodReviews		10.Clustering_AmazonFineFoodReviews
11.TruncatedSVD_AmazonFineFoods		11.TruncatedSVD_AmazonFineFoods
12.MLP_mnist		12.MLP_mnist
13.CNN_mnist		13.CNN_mnist
14.LSTM_amzn		14.LSTM_amzn
16.taxi_prediction		16.taxi_prediction
18.Netflix		18.Netflix
2.assign_amzn_fine_food_review_tsne		2.assign_amzn_fine_food_review_tsne
22.SQL_imdb		22.SQL_imdb
3.KNN_AmazonFineFoodReviewsPreProcessing		3.KNN_AmazonFineFoodReviewsPreProcessing
4.NaiveBayes_AmazonFineFoodReviews		4.NaiveBayes_AmazonFineFoodReviews
5.LogisticRegression_AmazonFineFoodReviews		5.LogisticRegression_AmazonFineFoodReviews
6.SGD_implementation		6.SGD_implementation
7.SVM_AmazonFineFoodReviews		7.SVM_AmazonFineFoodReviews
8.DT_AmazonFineFoodReviews		8.DT_AmazonFineFoodReviews
9.Ensemble_AmazonFineFoodReviews		9.Ensemble_AmazonFineFoodReviews
.gitignore		.gitignore
LICENSE		LICENSE
README.md		README.md
requirements.txt		requirements.txt

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