Atcold/NYU-DLSP20 resource
NYU Deep Learning Spring 2020 observed · 2026-08-28
Health v2 · maintenance only
35/100
- Activity 27
- Release rhythm 8
- Longevity 100
Flags: no_license
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 2977
- days_rel: n/a
- days_push: 443
- n_releases_24m: 0
Adoption not part of the score
6810 stars · 2231 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded
NYU Deep Learning Spring 2020 course materials by Yann LeCun and Alfredo Canziani, including Jupyter notebooks, slides, and videos. Covers CNNs, RNNs, energy-based models, GANs, transformers, and graph convolutional networks.
Use cases
- learn deep learning from scratch
- understand CNNs and RNNs with PyTorch notebooks
- study energy-based models and GANs
- follow a university-level deep learning course online
- practice backpropagation and autograd
- learn transformers and attention
When to choose
- you want free lecture videos paired with runnable PyTorch notebooks
- you prefer theory plus hands-on practicum exercises
When to avoid
- you need current SOTA techniques past 2020
- you want a production framework rather than course material
Facets
learning-resource · maturity maintenance
deep-learning machine-learning deep-learning tutorials python cross-platform jupyter-notebooks pytorch course-material yann-lecun neural-networks
2 sources
- readme: https://github.com/Atcold/NYU-DLSP20 · fetched 2026-08-28 · 66eea79479c8
- homepage: https://atcold.github.io/NYU-DLSP20/ · fetched 2026-08-29 · 5f2f671ed645
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| Atcold/NYU-DLSP20 | main | 35 |
For agents
markdown · JSON · MCP: product_card(name="Atcold/NYU-DLSP20")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem