# hunkim/PyTorchZeroToAll

Simple PyTorch Tutorials Zero to ALL!

Repository: https://github.com/hunkim/PyTorchZeroToAll
Canonical: https://ross.abutalabs.com/products/pytorchzerotoall
Homepage: http://bit.ly/PyTorchZeroAll
Language: Python
License Family: other
Topics: deeplearning, pytorch, python, tutorial, basic
Last push: 2024-03-23T08:23:14+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3255, "days_push": 893, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 3978, forks 1188 (observed 2026-08-28T04:08:30.959744+00:00)

## What it is
A collection of PyTorch tutorial materials including lecture slides and video lectures, designed as a quick 3-4 day crash course for HKUST students. It covers topics from linear models and gradient descent through CNNs, RNNs, and Seq2Seq models.

## Use cases
- learn pytorch from scratch
- pytorch tutorial for beginners
- deep learning crash course materials
- understand backpropagation and autograd in pytorch
- learn cnn and rnn with pytorch
- find pytorch lecture slides and videos

## When to choose
- you want a short, structured introduction to PyTorch fundamentals
- you prefer learning from slides paired with video lectures
- you are a student or beginner needing quick 3-4 day coverage of deep learning basics

## When to avoid
- you need up-to-date coverage of modern PyTorch APIs and features
- you want production-grade code or a maintained library
- you need advanced topics like transformers or large-scale training

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: machine-learning, deep-learning
- domain: deep-learning, machine-learning, tutorials
- platform: python
- tags: pytorch, tutorial, lecture-slides, video-lectures, beginner

## Member repositories
- hunkim/PyTorchZeroToAll (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:30.959744+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 2026-08-29T18:24:18.444216+00:00, confidence not recorded.
  - readme: https://github.com/hunkim/PyTorchZeroToAll (fetched 2026-08-28T04:08:30.959744+00:00, sha ff333f7c4511)
  - homepage: http://bit.ly/PyTorchZeroAll (fetched 2026-08-29T09:17:37.797283+00:00, sha f5250e6e738d)
- Data as of 2026-08-30T08:39:29.467469+00:00.