How much math knowledge do you need for machine learning and deep learning?
Some people say not much.
Others say a lot.
Both are correct, depending on what you want to achieve.
But theres no escaping the mathematical foundations ofmachine learning.
In this post, I will introduce some of my favorite machine learning math resources.
I would argue that you need a lot more than that.
There are plenty of good textbooks, online courses, and blogs that explore these topics.
But my personal favorite isKhan Academys math courses.
And its free, which makes it even better.
I recommend thelinear algebracoursein particular.
But they discuss the same concepts youll encounter in machine learning books and whitepapers.
Khan includes precalculus, differential calculus, and integral calculus courses that cover the foundations.
There are also several statistics courses in Khan Academys platform, and there are some overlaps between them.
To be clear, Khan Academys courses are not a replacement for the math textbook and classroom.
They are not very rich in exercises.
There are more specialized resources for that.
My favorite isMathematics for Machine Learning.
The book is split into two parts.
The first part is mathematical foundations, which is basically a revision of key linear algebra and calculus concepts.
If you have a strong foundation, this part will be a pleasant read.
Itll become much easier.
The second part of the book focuses on machine learning mathematics.
Youll get into topics such as regression, dimensionality reduction, support vector machines, and more.
Instead, we aim to provide the necessary mathematical skills to read those other books.
For a more advanced take on deep learning, I recommendHands-on Mathematics for Deep Learning.
This book also contains an intro on linear algebra, calculus, and probability and statistics.
Again, this section is for people who just want to jar their memory.
Its not a basic introductory book.
These are concepts that youll encounter in most books on machine learning and deep learning.
When should you learn machine learning mathematics?
Agreeably, mathematics is not the most fun way to start machine learning education, especially if youre self-learning.
UdemysMachine Learning A-Zis an online course that combines coding with visualization in a very intuitive way.
I would recommend starting with one or two of the above-mentioned books and courses.
In my experience, the mathematics of machine learning is an ongoing educational experience.
Always look for new ways to hone your skills.
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