Machine Learning

These notes originated from Yale’s S&DS665: Intermediate Machine Learning as taught by Prof. John Lafferty in Fall 2022. The course covers sparse regression, non-parametric regression, neural networks, convolutional neural networks, gaussian processes, variational inference, variational autoencoders, graph methods, reinforcement learning, Q-learning, deep reinforcement learning, policy iteration and gradient methods, actor-critic methods, sequence models, recurrent neural netowrks, GRUs, and transformers.

1. Course Notes: Handwritten notes from S&DS665: Intermediate Machine Learninc