# ZeweiChu/PyTorch-Course

JULYEDU PyTorch Course

Repository: https://github.com/ZeweiChu/PyTorch-Course
Canonical: https://ross.abutalabs.com/products/pytorch-course
Language: Jupyter Notebook
License Family: other
Last push: 2021-02-01T08:41:00+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": 2724, "days_push": 2039, "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 1081, forks 501 (observed 2026-08-28T04:03:30.900898+00:00)

## What it is
A Jupyter Notebook-based PyTorch tutorial course originally written for PyTorch 0.4.0, created by Zewei Chu for JULYEDU. The material is now outdated relative to modern PyTorch versions and the repository appears unmaintained.

## Use cases
- learn pytorch basics through notebooks
- pytorch tutorial for beginners
- study deep learning course material in python
- understand pytorch tensor and autograd concepts
- find example pytorch training code to adapt

## When to choose
- you want a structured notebook-based introduction to PyTorch fundamentals
- you are following the JULYEDU course and need the companion code
- you don't mind adapting old PyTorch 0.4 code to newer versions

## When to avoid
- you need up-to-date PyTorch 1.x/2.x idioms and APIs
- you want actively maintained learning material
- you need a license permitting reuse of the code

## Facets
- artifact type: learning-resource
- maturity: abandoned
- function: machine-learning, deep-learning, developer-tools
- domain: deep-learning, machine-learning, tutorials
- platform: python
- tags: pytorch, jupyter-notebook, course, tutorial, chinese-language

## Member repositories
- ZeweiChu/PyTorch-Course (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:30.900898+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 2026-08-30T06:51:19.146581+00:00, confidence not recorded.
  - readme: https://github.com/ZeweiChu/PyTorch-Course (fetched 2026-08-28T04:03:30.900898+00:00, sha ba105c07fdcb)
- Data as of 2026-08-30T08:39:29.467469+00:00.