karpathy/examples — explained in plain English
Analysis updated 2026-07-17 · repo last pushed 2018-05-15
Learn to build an image recognition model by running the handwritten digit recognition example.
Study a working language modeling or translation example to understand text-based deep learning.
Use the reinforcement learning pole-balancer example as a template for training a game-playing AI.
Reference stripped-down, production-style model code when adding AI features to an application.
| karpathy/examples | nvlabs/isaaclabeureka | orange2019220/relupruner | |
|---|---|---|---|
| Stars | 138 | 138 | 139 |
| Language | Python | Python | Python |
| Last pushed | 2018-05-15 | 2025-10-28 | — |
| Maintenance | Dormant | Quiet | — |
| Setup difficulty | moderate | moderate | moderate |
| Complexity | 3/5 | 4/5 | 4/5 |
| Audience | researcher | researcher | researcher |
Figures from each repo's GitHub metadata at analysis time.
A curated collection of runnable PyTorch code examples for vision, text, and reinforcement learning tasks, built as a hands-on cookbook for learning machine learning by Andrej Karpathy.
Mainly Python. The stack also includes Python, PyTorch.
Dormant — no commits in 2+ years (last push 2018-05-15).
Setup difficulty is rated moderate.
Mainly researcher.
This repo across BitVibe Labs
double-check against the repo, no cap.