rth/dl-lectures-labs — explained in plain English
Analysis updated 2026-07-17 · repo last pushed 2026-02-06
Follow a structured curriculum to learn deep learning fundamentals from scratch.
Run hands-on notebooks covering image recognition, object detection, and NLP.
Reuse or adapt the slides and labs to teach your own deep learning course.
Fine-tune a pre-trained image model or build a recommender system as a guided exercise.
| rth/dl-lectures-labs | ypwhs/carnd-lanelines-p1 | mjib007/revenue-yoy-backtest | |
|---|---|---|---|
| Stars | 15 | 15 | 14 |
| Language | Jupyter Notebook | Jupyter Notebook | Jupyter Notebook |
| Last pushed | 2026-02-06 | 2017-01-20 | — |
| Maintenance | Maintained | Dormant | — |
| Setup difficulty | easy | moderate | easy |
| Complexity | 2/5 | 2/5 | 1/5 |
| Audience | researcher | vibe coder | general |
Figures from each repo's GitHub metadata at analysis time.
Notebooks run instantly in-browser via Binder, no local setup required.
A free deep learning course with slides and hands-on Jupyter notebooks covering neural network basics, image recognition, and NLP.
Mainly Jupyter Notebook. The stack also includes Jupyter Notebook, Keras, Binder.
Maintained — commit in last 6 months (last push 2026-02-06).
Free to use and modify under standard open licenses, including for teaching or learning purposes.
Setup difficulty is rated easy, with roughly 5min to a first successful run.
Mainly researcher.
This repo across BitVibe Labs
double-check against the repo, no cap.