Tal Kachman

FAQ

Machine Learning Book Recommendations

"Elements of Statistical Learning"

Written by the people who made most of the landmark developments in the field

"Probabilistic Machine Learning"

Fantastic background into the more CS world of machine learning

"Understanding Machine Learning: From Theory to Algorithms"

A bit more mathematical with strong emphasis on optimization and algorithmic execution

"Foundations of Machine Learning"

Very strong emphasis on mathematical aspects such as PAC learning

Stanford course on Machine Learning

YouTube video series

Deep Learning Recommendations

"Neural Networks and Deep Learning"

Stellar introduction from scratch

"Deep Learning"

Nice introduction overview

Introduction to Deep Learning tutorials

YouTube playlist

Stanford Computer Vision course

Deep Learning at Oxford course by Nando de Freitas

"The Principles of Deep Learning Theory"

In-depth perspective

Radboud Related Teaching/Advising

Recommends studying math fundamentals: linear algebra, calculus, optimization, statistics and probability

Provides guidance on thesis supervision and reading

Suggests information for prospective students is available on another page