[Resources] ML

Getting into ML

• You need to build things.

Start small, simple genetic algorithm simulation called Smart Rockets, by CodingTrain:

• https://www.youtube.com/watch?v=9zfeTw-uFCw&list=PLRqwX-V7Uu6bJM3VgzjNV5YxVxUwzALHV
• First 8 vids walk you through basics of genetic algorithm.

Neural Networks

• Introduction to Neural Networks by The Coding Train
• Andrej Karpathy

Other Resources

The Little Book of Deep Learning

The Nature of Code by Daniel Shiffman

• Programming + concepts related to making interactive media projects (pixels, data, sound, networking, 3D, and more).

Ludwig’s Resources

You want to know how ML works beneath the frameworks:

• “Understanding Deep Learning” by Simon J. D. Prince
• “100 Page Machine Learning Book” by Andriy Burkov
• “The Little Book of Deep Learning”

If you lack the math skills:

• “Mathematics for Machine Learning” by Marc Peter Deisenroth, …
• “Linear Algebra Done Right” by Sheldon Axler
• 3Brown1Blue videos

Want to dive into ML:

• FastAI Book
• FastAI Video course

LLMs:

• Andrej Karpathy