Many of my subscribers have asked for some resources to help get them on a path for better understanding with regards to inference and learning. As many individuals have various learning styles there are both reading and video (I would recommend both).
- Book: Murphy — Chapter 1 — Introduction
- Book: Bishop — Chapter 1 — Introduction
- Video: Christopher Bishop — Embracing Uncertainty: The New Machine Intelligence
- Video: Sam Roweis — Machine Learning, Probability and Graphical Models, Part 1
- Video: Iain Murray — Introduction to Machine Learning, Part 1
- Video: Neil Lawrence — What is Machine Learning?
Books mentioned above:
Machine Learning: A Probabilistic Perspective Kevin P. Murphy, MIT Press, 2012.
Pattern Recognition and Machine Learning Christopher M. Bishop, Springer, 2006. An excellent and affordable book on machine learning, with a Bayesian focus. It covers fewer topics than the Murphy book, but goes into more depth on the topics it covers.
If you have resources that you think that I missed, please let me know. If there is a resource that you particularly enjoyed I would like to hear from you as well.
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