Who is this book for?
If you are starving to get deeper insights while reading Deep Learning or Machine Learning papers, but are a little bit rusty with Linear Algebra, then
Basics of Linear Algebra for Machine Learning by Jason Brownlee from Machine Learning Mastery is just for you!
What this book is all about?
- This book is a gentle introduction into Linear Algebra for people interested in machine learning.
- As all books written by Jason it features Python hands-on practical approach.
- It comes with a number of exercises for each chapter.
- It has extensive references for each chapter too.
- It feels like a good tool for beginner practitioners to Deep or Machine Learning.
Additional resources that may come in handy
I personally liked two books that Jason mentioned in his latest book
- No Bullshit Guide To Liner Algebra which is the best book of its kind in my opinion having examples from quantum physics and more.
- Deep Learning book by Ian Goodfellow, Yoshua Bengio an Aaron Courville. This book is more or less currently the Bible of Deep Learning.
What are you waiting for?
Grab one of the books and get amazed by applied math and Deep Learning.