this repository contains various completed courses and their associated code implementations as well as some links
Machine Learning (Stanford CS229) | course-site
This course provides a broad introduction to machine learning and statistical pattern recognition. Topics include: supervised learning (generative/discriminative learning, parametric/non-parametric learning, neural networks, support vector machines); unsupervised learning (clustering, dimensionality reduction, kernel methods); learning theory (bias/variance tradeoffs, practical advice); reinforcement learning and adaptive control.
Deep Unsupervised Learning 2019 Berkley | course-site
NLP: From Languages to Information - Stanford
Natural Language Processing with Deep Learning - Stanford