# deep-learning-with-pytorch/dlwpt-code

Code for the book Deep Learning with PyTorch by Eli Stevens, Luca Antiga, and Thomas Viehmann.

Repository: https://github.com/deep-learning-with-pytorch/dlwpt-code
Canonical: https://ross.abutalabs.com/products/dlwpt-code
Homepage: https://www.manning.com/books/deep-learning-with-pytorch
Language: Jupyter Notebook
License Family: other
Topics: pytorch, deep-learning, deep-neural-networks, python, python3
Last push: 2024-07-25T10:58:29+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 3077, "days_push": 769, "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 5232, forks 2151 (observed 2026-08-28T04:09:13.459829+00:00)

## What it is
The official companion code repository for the Manning book 'Deep Learning with PyTorch' by Stevens, Antiga, and Viehmann. It contains Jupyter Notebook examples that teach deep learning fundamentals and PyTorch through a real-life project.

## Use cases
- learn deep learning with pytorch from scratch
- find code examples for the deep learning with pytorch book
- hands-on pytorch tutorial notebooks
- understand neural network fundamentals with pytorch
- follow a real-world deep learning project end to end
- get started with pytorch as a developer

## When to choose
- you are reading the book and want its runnable code
- you are a developer or data scientist new to PyTorch wanting guided examples
- you prefer learning through Jupyter notebooks with a project-based approach

## When to avoid
- you need a production deep learning framework or library
- you want coverage of recurrent neural networks or the full PyTorch API
- you need actively maintained, up-to-date tutorials independent of the book

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

## Member repositories
- deep-learning-with-pytorch/dlwpt-code (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:13.459829+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 2026-08-29T17:59:38.650571+00:00, confidence not recorded.
  - readme: https://github.com/deep-learning-with-pytorch/dlwpt-code (fetched 2026-08-28T04:09:13.459829+00:00, sha bd1357affa03)
  - homepage: https://www.manning.com/books/deep-learning-with-pytorch (fetched 2026-08-29T08:54:58.532752+00:00, sha 91207aef0916)
  - site_page: https://www.manning.com/faq (fetched 2026-08-29T08:54:58.535280+00:00, sha 9e27304d7757)
- Data as of 2026-08-30T08:39:29.467469+00:00.