Learning path for ML, DL, RL, and recommendation
20170522
This is a record of my learning.
Much of our future is related to AI. It’s time to understand and apply current AI to engineering problems.
Machine Learning course - Andrew Ng
Neural Networks for Machine Learning - Geoffrey Hinton, University of Toronto
Deep learning on Udacity, this is a hands-on course. I am in the middle of this course.
I needed a refresher on statistics: Basic Statistics - Matthijs Rooduijn, Emiel van Loon, University of Amsterdam
When learn a new thing, I prefer knowing thoroughly. After going through the courses, I found books give me more confidence.
“Introduction to Machine Learning” by Ethem Alpaydin. This book is highly recommended.
“Recommender Systems Handbook” by Francesco Ricci, Lior Rokach etc. It’s a recommender system bible.
“Deep Learning” by Ian Goodfellow. I am not able to go through this book yet. But it’s been recommended by many.
“Reinforcement Learning: An Introduction” by Sutton, Barto
I have also been getting my next steps by looking at this Quora answer. “How do I learn deep learning in 2 months?”
