Mathematics for Machine Learning Resources

Mathematics for Machine Learning Resources

Every day, computational fields like machine learning, artificial intelligence, neuroscience, cryptography, etc. are making great progress. Anyone pursuing a career in all such fields might be looking for a solid foundation. If we dig deeper, we often trace back to the Queen of Science- Mathematics.

A solid foundation of the math concepts will be useful in not only understanding today’s technology but also let you create tomorrow’s. The huge interest in data science, machine learning, and artificial intelligence attracted people from multiple disciplines into these fields. There are a good number of resources freely available on the internet for them on the math foundations.

This is a curated list of some of my favorite resources.

  1. Essence of Calculus by Grant Sanderson
  2. Essence of Linear Algebra by Grant Sanderson
  3. Math Better Explained YouTube
  4. Multivariable Calculus by Grant Sanderson
  5. Crazy Muse YouTube
  6. Mirror Neuron MML
  7. Highlights of Calculus, Gilbert Strang
  8. Neuroscience Supplements by Rich Pang
  9. Coursera Mathematics for Machine Learning Linear Algebra
  10. Coursera Mathematics for Machine Learning Multivariate Calculus
  11. Coursera Mathematics for Machine Learning PCA Machine Learning
  12. CBMM Tutorial Linear Algebra by Joe Olson
  13. CBMM Probability Tutorial Andrei Barbu
  14. Introduction to Higher Mathematics by Bill Shillito

There are plenty of other resources. But these are the ones I have gone through and liked the most. If you are a visual person like me and prefer a mix of visuals, intuitions, and fundamental ideas, I am sure you will like these.

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