The Math of Intelligence

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What is it?

This is a list of resources you need to learn the Math of Machine Learning.

How to use it

I have divided the resources into categories.

Why Mathematics is important in Machine Learning?

Watch this video where Siraj Raval explains the big 4 math disciplines that make up Machine Learning.

The High Schoolers Guide to the Math of Intelligence:

This list is meant to serve both High Schoolers and those who feel their math is a bit rusty. This is a systematic approach to learning the Math required for Machine Learning.

Prerequisite Knowledge:

Linear Algebra:

Books:
  •  The Manga Guide to Linear Algebra: Probably the best book to start Linear Algebra with. The Manga style makes the material easy to leaf through and learn in a quick and enjoyable way.
  •  Introduction to Linear Algebra - Gilbert Strang: This book is much more detailed as compared to the previous one. Gilbert Strang also have MOOC on MIT OCW which is linked below in the MOOCs section. It's highly recommended to use this book with the MOOC.
  •  Linear Algebra: A Modern Introduction: This super expensive book can be a replacement for Strang's book which a few people find "too dry", as it is easy to read and understand, topics are very well-organized in a logical way. Every chapter begins with a problem that introduces informally the concepts that will be addressed in the sections.
MOOCs/Videos:

Calculus:

Books:
I won't recommend reading more books about Calculus since our focus is to learn a very specific part of Calculus which is required for Machine Learning, we don't want to gain PhD level understanding of Calculus.
MOOCs/Videos:

Statistics & Probability:

MOOCs:
Books:

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