Projects from CS:5430 Machine Learning. Each project is in its own folder and contains the pdf of the homework the project comes from.
Project 1: Document Term Matrix
Short project using numpy to create a document term matrix that helps to identify which documents have the most words in common with a given query. This projects goal is to emulate a naive search engine.
Project 2: Boston House Prices
Use scikit-learn to predict Boston Housing prices.
Project 3: kNN and Naive Bayes
Use scikit learn to do kth nearest neighbor classification, Naive Bayes implementation not included
Project 4: Logistic Regression and Support Vector Machine
Used liblinear and scikit learn to do classification, also implemented 3 preprocessing methods: scaling, standardization and normalization.