# Atcold/NYU-DLSP20

NYU Deep Learning Spring 2020

Repository: https://github.com/Atcold/NYU-DLSP20
Canonical: https://ross.abutalabs.com/products/nyu-dlsp20
Homepage: https://atcold.github.io/NYU-DLSP20/
Language: Jupyter Notebook
License: NOASSERTION
License Family: other
Topics: jupyter-notebook, pytorch, deep-learning, neural-nets
Last push: 2025-06-16T19:16:24+00:00

## Health v2 (maintenance only)
Score: 35/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 27, release rhythm 8, longevity 100
- inputs: {"age_days": 2977, "days_push": 443, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 6810, forks 2231 (observed 2026-08-28T04:09:48.776055+00:00)

## What it is
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
- artifact type: learning-resource
- maturity: maintenance
- function: deep-learning, machine-learning
- domain: deep-learning, tutorials
- platform: python, cross-platform
- tags: jupyter-notebooks, pytorch, course-material, yann-lecun, neural-networks

## Member repositories
- Atcold/NYU-DLSP20 (main) score 35

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:48.776055+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:42:01.434313+00:00, confidence not recorded.
  - readme: https://github.com/Atcold/NYU-DLSP20 (fetched 2026-08-28T04:09:48.776055+00:00, sha 66eea79479c8)
  - homepage: https://atcold.github.io/NYU-DLSP20/ (fetched 2026-08-29T08:38:02.744092+00:00, sha 5f2f671ed645)
- Data as of 2026-08-30T08:39:29.467469+00:00.