Implementation of Machine Learning algorithms using numpy in Python. The exercise was done as part of homeworks given at Columbia's Machine Learning (COMS W4721) class conducted by Dr. John Paisley
The algorithms implemented are:
- Ridge Regression (hw1)
- Logistic Regresssion (hw2)
- K-Nearest-Neighbors Classifier (hw2)
- Naive Bayes Classifier (hw2)
- Gaussian Process for Regression (hw3)
- Gradient Boosted Linear Classifier (hw3)
- K-Means Clustering (hw4)
- Matrix Factorization (hw4)
- Markov Chain (hw5)
- Nonnegative Matrix Factorization (hw5)