Machine Learning Part 1: Supervised Learning and Neural Networks
A survey of machine learning topics including supervised, unsupervised, clustering and dimensionality reduction, and reinforcement learning
All things related to my OMSCS masters program
Machine Learning Part 3: Unsupervised Learning & Dimensionality Reduction
Exploring clustering, Gaussian mixtures, and dimensionality reduction methods (PCA, ICA, RP, RF) on the Wine and Abalone datasets.
Machine Learning Part 4: Markov Decision Processes & Reinforcement Learning
Exploring Value Iteration, Policy Iteration, and Q-Learning in stochastic grid worlds, comparing convergence, rewards, timing, and behavior across easy and hard MDP environments.
SenseCourse
A look at using Watson AI to select courses based on your personality