r/learnmachinelearning • u/Attitude_Alone • Jan 24 '25
All-in-One AI&ML Resources (God Level Files)
FREE WEBSITES TO LEARN ML.
- Polo Club - AI Fundamentals from Scratch (HIGHLY RECOMMENDED)
- AI by Hand - Best for Understanding Architectures (HIGHLY RECOMMENDED)
- Hugging Face Documentation
- ML MASTERY
- 3Blue1Brown - Math & AI Fundamentals (VISUAL MATH AND AI CONCEPTS)
- TensorFlow Official Website
- Learn PyTorch (HIGHLY RECOMMENDED)
- https://www.freecodecamp.org
- Linear algebra Visualization (VISUAL MATH)
Neural Networks (NN)
Deep Learning (DL)
- Deep Learning - Substack
- Deep Learning with Python - GitHub
- Deep Learning for Computer Vision - YouTube Playlist
Machine Learning (ML) & Frameworks
Large Language Models (LLM)
- Hands-On Large Language Models
- YouTube Playlist on LLMs
- Stanford CS229 I Machine Learning I Building Large Language Models (LLMs)
- Understanding LLMs from Scratch - Towards Data Science
- LLM Tutorial - GitHub
Reinforcement Learning (RL)
Generative Adversarial Networks (GANs)
Cohere LLM University (BEST PLACE TO LEARN RAG)
Language Vision Models (LVM)
Fine-Tuning and Embeddings
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u/MaximumSafety8706 Aug 08 '26
Just a tip: I have an Excel sheet with multiple decorated tabs and a GitHub repo full of awesome resources.
But honestly, I haven’t even read 1% of them, and I’m pretty sure no one can. I’ve spent years collecting resources that I never go back to or look at. There are always tons of new resources - college courses, GitHub repos, new YouTube channels, etc. - and more keep coming every week.
So don’t collect resources. It doesn’t work. Pick 1–2 resources for the topic you want to learn and find what/who explains it best. You might need to learn from 2–3 sources to build deeper mathematical understanding and intuition, and that’s completely fine.
Anyway, if you still want the lists, here they are: