Are there any videos or other books/notes that anyone has come across that follow Pattern Recognition and Machine Learning by Chris Bishop? I bought this book to learn Machine Learning and am having some trouble getting through it.
Bishop is a great book. I hope these suggestions help with your study:
- The author himself has posted some slides for Chapters 1, 2, 3 & 8, as well as many solutions.
- A reading group at INRIA have posted their own slides covering every chapter.
- João Pedro Neto has posted some notes and workings in R here. (Scroll down to where it says "Bishop's Pattern Recognition and ML")
- Many introductory machine learning courses use Bishop as their textbook. Googling gives a few different ones; have a look and see which topics and focus you prefer.
I would recommend these resources to you:
- Tom Mitchell: Carnegie Mellon University
- (Only for Supervised Learning and follows Bishop) Pattern Recognition: Indian Institute of Science (I personally like this course as I have attended it, but this course requires you to know probability theory.)
Both the courses are maths oriented, for a lighter course on machine learning would be "Machine Learning" by Udacity