# L1aoXingyu/code-of-learn-deep-learning-with-pytorch

This is code of book "Learn Deep Learning with PyTorch"

Repository: https://github.com/L1aoXingyu/code-of-learn-deep-learning-with-pytorch
Canonical: https://ross.abutalabs.com/products/code-of-learn-deep-learning-with-pytorch
Homepage: https://item.jd.com/17915495606.html
Language: Jupyter Notebook
License Family: other
Topics: pytorch, pytorch-tutorials-cn, pytorch-tutorial
Last push: 2024-03-04T08:38:10+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3361, "days_push": 912, "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 2875, forks 1238 (observed 2026-08-28T04:07:27.322960+00:00)

## What it is
Companion Jupyter Notebook code repository for the Chinese book 'Learn Deep Learning with PyTorch' (深度学习入门之PyTorch). It covers PyTorch basics, neural networks, optimizers, CNNs, and other deep learning fundamentals through runnable notebooks.

## Use cases
- learn pytorch from scratch
- deep learning tutorial notebooks
- understand autograd and dynamic graphs
- implement linear and logistic regression in pytorch
- compare optimizers like sgd adam rmsprop
- build convolutional neural networks with pytorch

## When to choose
- you are a beginner learning deep learning with PyTorch
- you want runnable notebook examples accompanying a structured book
- you prefer Chinese-language learning materials

## When to avoid
- you need production-ready deep learning code
- you require a maintained library with a license
- you need coverage of the latest PyTorch APIs without checking for bugs

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: deep-learning, machine-learning
- domain: deep-learning, machine-learning, tutorials
- platform: python, cross-platform
- tags: pytorch, jupyter-notebooks, chinese, book-companion, tutorials

## Member repositories
- L1aoXingyu/code-of-learn-deep-learning-with-pytorch (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:27.322960+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 2026-08-30T07:35:47.823619+00:00, confidence not recorded.
  - readme: https://github.com/L1aoXingyu/code-of-learn-deep-learning-with-pytorch (fetched 2026-08-28T04:07:27.322960+00:00, sha 36b8f449b3c1)
  - homepage: https://item.jd.com/17915495606.html (fetched 2026-08-29T09:51:17.555138+00:00, sha 879e3d5a9c5e)
- Data as of 2026-08-30T08:39:29.467469+00:00.