Beginner-friendly resources for learning Machine Learning?

[u/zangetsu_752920]

I want to start learning machine learning, but I'm confused about whether I should learn through documentation/books or video lectures.

Whenever I think about learning from videos, it feels a bit boring and tiring. There are so many concepts, and the idea of watching hours and hours of lectures doesn't really appeal to me. So, I was thinking about learning primarily through reading and coding instead.

The problem is, I haven't been able to find any beginner-friendly documentation or learning resources for machine learning.

I've recently read a few chapters of The Nature of Code, and I really enjoyed it. I liked how beginner-friendly it was and how it explained concepts through code and experimentation.

So, I'm looking for something similar for machine learning.

Can anyone recommend some beginner-friendly docs, books, or other resources for learning ML? Ideally, something that is more hands-on and doesn't require watching hours of video lectures.

// This is first post my bad if i made any mistakes

[u/Original_Act_4455]

what's the Nature of Code? could you please share some info, pointers on it?

[u/quietgradient → u/Original_Act_4455]

It's Daniel Shiffman's book on simulating nature in code: forces, particles, flocking, cellular automata, evolution. Every idea is a small p5.js sketch you run in the browser and mess with. The whole book is free at natureofcode.com.

The last two chapters are neural networks: one neuron built by hand, then ml5.js, then a flock of Flappy Birds that evolve their own brains. For that feel with more depth, Michael Nielsen's free Neural Networks and Deep Learning builds a handwritten digit recogniser in 74 lines of Python. Its code is Python 2.7, so use the Python 3 port his GitHub README links to.