Journey to being good at machine learning. Essentially here are the books I am reading at the moment and I thought it would be helpful to keep track and maybe review them as I go along.
A bit about my background. I did an undergraduate degree in micribiology but took many of my electives in maths and programming. Currently doing my honours in bioinformatics and trying to learn more about machine learning and statistics. If you are someone not from a strictly computer science background interested in learning more about AI and machine learning feel free to use this page as a resource to find good books and information.
This is a new version of the book Elements of Statistical Learning(ESL). However, ESL was intended for individuals with advanced training in the mathematical sciences so this is similar however with a focus on the methods and less on the mathematical details.
I am really enjoying the labs because it gives you an opportunity to really try out the theory that you learn in the chapter. Normally I'm actually fine being quite a theoretical person but I have been pleasantly surprised by how much fun it is to do the labs. The best part is actually just being able answer questions about the datasets that you work through e.g. Is there a relationship between school class sizes and property values in a neighbourhood?
Deep learning in python
Deep learning