#196 · Primary category: Education & Research
introtodeeplearning
Lab Materials for MIT 6.S191: Introduction to Deep Learning
Project last updated:01/04/26
GitHub Stars
8.8K
Forks
4.6K
Contributors
32
License
MIT
Why we included this project
Learning deep learning by writing code is easier with MIT's 6.S191 materials, and this repository is where the labs live. Each notebook pairs with a public lecture video and slides, so you can watch a topic explained and then try it in code in the same sitting. The labs move from the fundamentals into applied areas like computer vision, reinforcement learning, and music generation, with exercises you complete by filling in TODO cells. Since everything runs in Google Colab, the only setup is a browser and a Google account, no local install to fight. The self-paced structure suits independent study, and the progression is clean enough that a small team could work through it together to get up to speed on modern deep learning.
Articles for this project
No articles for this project yet.
To suggest a topic or contribute an article, contact us.
Related projects in this category
prompts.chat
f.k.a. Awesome ChatGPT Prompts. Share, discover, and collect prompts from the community. Free and open source — self-host for your organization with complete privacy.
JavaGuide
Java Interview & Backend General Interview Guide, covering computer fundamentals, databases, distributed systems, high concurrency, system design, and AI application development.
system-prompts-and-models-of-ai-tools
A curated collection of system prompts, internal tools, and AI models from popular AI assistants and coding agents.
30-seconds-of-code
Coding articles to level up your development skills
generative-ai-for-beginners
21 Lessons, Get Started Building with Generative AI