I followed Andrew Ng's Machine Learning course on Coursera during June, 2019. This repository contains programming exercises from this course. Topics covered include:
- Supervised learning: linear regression, logistic regresiion, neural networks, SVMs
- Unsupervised learning: k-means, PCA, anomaly detection
- Special applications: recommender systems, large scale machine learning
- Advice on building ML systems: bias/variance, learning curves, error analysis, ceiling analysis