ML Projects Understanding Bayesian Networks Coding different types of bayes nets and learning their structure and parameters. Collaborative Filtering Implemented an efficient algorithm for collaborative filtering and used it to recommend movies to users based on their ratings. A Deep Dive into Decision Trees and Random Forests Coding a decision tree and a random forest classifier from scratch and analyzing the performance of the classifiers on different datasets. KMeans Clustering for Image Compression Implementing KMeans Clustering and applied it for image compression and analyzed the compression ratio and the quality of the compressed image. Understanding Logistic Regression and Naive Bayes Coding the Logistic Regression and Naive Bayes classifier from scratch and analyzing the performance on identifying Ham vs Spam email.
