The Best Machine Learning Resources

A compendium of resources for crafting a curriculum on artificial intelligence, machine learning, and deep learning.

This article is an addendum to the series Machine Learning for Humans 🤖👶 , a guide for getting up-to-speed on machine learning concepts in 2-3 hours.

General advice on crafting a curriculum

Going to school for a formal degree program for isn’t always possible or desirable. For those considering an autodidactic alternative, this is for you.

1. Build foundations, and then specialize in areas of interest.

You can’t go deeply into every machine learning topic. There’s too much to learn, and the field is advancing rapidly. Master foundational concepts and then focus on projects in a specific domain of interest — whether it’s natural language understanding, computer vision, deep reinforcement learning, robotics, or whatever else.

2. Design your curriculum around topics that personally excite you.

Motivation is far more important than micro-optimizing a learning strategy for some long-term academic or career goal. If you’re having fun, you’ll make fast progress. If you’re trying to force yourself forward, you’ll slow down.

We’ve included resources that we explored personally or came highly recommended. This list is not meant to be exhaustive. There are endless options, and too much choice is counterproductive. But if we’re missing a great resource that belongs here, please reach out

Foundations

Programming

Linear algebra

Probability & statistics

Calculus

Machine learning

Deep learning

Reinforcement learning

Artificial intelligence

Artificial intelligence safety

Newsletters

Advice from others

“You take the blue pill, the story ends. You wake up in your bed and believe whatever you want to believe. You take the red pill, you stay in Wonderland, and I show you how deep the rabbit hole goes.” — Morpheus

Good luck!