Useful resources for neural networks and machine learning (compiled by the wonderful Tony Clark).
Courses
Books
-
Machine Learning by Tom Mitchell (Amazon link). Historically this is the gold standard; however, it is too expensive to be the required textbook, particularly given that its age means it does not cover several important topics. You may be able to find used versions for a reasonable price; there is also a reserved copy in the Cornell Library.
-
Introduction to Machine Learning by Ethem Alpaydin (Amazon link). If you are looking to purchase a hard copy, this is the one I recommend as it is reasonably priced and a good textbook. It is also available as an ebook available for free through the library’s ProQuest account.
-
Pattern Recognition and Machine Learning by Christopher Bishop
-
Machine Learning: A Probabilistic Perspective by Kevin Murphy (and the advanced topics book)
-
Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville