An introductory machine learning course from Washington University offered on Coursera, covering core ML concepts such as bias versus variance and Bayesian reasoning.

Commenters call it a solid foundation in ML and praise the lecturer as the best they have seen.

What commenters said (1)

1. RecommendsDzugaru2016in “How to Start Learning Deep Learning”

   If you ask me about ML I'll say that starting with convolutional nets for images is starting on the wrong side (end instead of beginning). Andrew Ng course is better, but still somewhat lacks theory and general ML insights.

   I'd recommend new Coursera Washington University ML course (https://class.coursera.org/machlearning-001/lecture) as a solid foundation. You'll learn key ML concepts (bias vs variance, bayes theory etc.) and the lector is simply the best I've seen.

   Following that Ian Goodfellow book http://www.deeplearningbook.org/ is very good.

   If you want to learn foundations of Reinforcement Learning I'd recommend Sutton & Barto https://webdocs.cs.ualberta.ca/~sutton/book/ebook/the-book.h...

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