Assessing the Performance of various Models.ipynb
Choosing features and metrics for nearest neighbor search.ipynb
Classification using Sentiment Analysis.ipynb
Deep Learning Assignment.ipynb
Documet retrieval using clustering.ipynb
Exploring Ensemble methods.ipynb
Exploring precision and recall .ipynb
Gradient Boosted tree.ipynb
Handling Overfitting in decision tree.ipynb
Identifying safe loans with decision trees.ipynb
Image Classification using Deep Learning.ipynb
Image Retrieval using Deep Features.ipynb
Implementing LASSO using coordinate descent.ipynb
Implementing Locality Sensitive Hashing from scratch.ipynb
Implementing binary decision trees.ipynb
Implementing logistic Regression from Scratch.ipynb
K-Nearest Neighbour for predicting house prices.ipynb
Logistic Regression with L2 regularization.ipynb
Logistic Regression_Linear Classifier.ipynb
Mercari Price Suggestion Lightgbm.ipynb
Multiple Regression Assignment 1.ipynb
Multiple Regression Assignment 2.ipynb
Overfitting_Demo_Ridge_Lasso.ipynb
Price optimization Part 1.ipynb
Price optimization Part 2.ipynb
Price optimization upgraded version.ipynb
Products_Recommender_1.ipynb
Products_Recommender_2.ipynb
Recommendation System.ipynb
Recommendation for Electronics products.ipynb
Ridge Regression via Gradient desecent.ipynb
Ridge regression using L2 penalty.ipynb
Simple Regression Assignment.ipynb
Training Logistic Regression via Stochastic Gradient Ascent.ipynb
Turi Getting Started with SFrames.ipynb
Using Lasso to select Features.ipynb
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