Ramakm/ai-hands-on
A group of notebooks and other files which can help you learn AI from scratch.
This collection of interactive guides helps you learn the core concepts of Artificial Intelligence from the ground up. You'll work through practical examples using Jupyter notebooks, covering everything from fundamental math to building neural networks, transformers, and systems for tasks like retrieving information and recognizing text. This resource is perfect for aspiring AI engineers or developers looking to upskill in AI.
1,068 stars. Actively maintained with 3 commits in the last 30 days.
Use this if you want a structured, hands-on approach to learn AI engineering, progressing from basic principles to advanced topics with practical code.
Not ideal if you are looking for a plug-and-play AI solution or an academic deep dive into theoretical AI research.
Stars
1,068
Forks
239
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Feb 14, 2026
Commits (30d)
3
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