# fchollet/deep-learning-with-python-notebooks

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

Repository: https://github.com/fchollet/deep-learning-with-python-notebooks
Canonical: https://ross.abutalabs.com/products/deep-learning-with-python-notebooks
Language: Jupyter Notebook
License: MIT
License Family: permissive
Last push: 2025-09-18T05:12:40+00:00

## Health v2 (maintenance only)
Score: 51/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 42, release rhythm 35, longevity 100
- inputs: {"age_days": 3284, "days_push": 349, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 20273, forks 9056 (observed 2026-08-28T04:11:29.864071+00:00)

## What it is
A collection of Jupyter notebooks containing the runnable code samples from the book 'Deep Learning with Python' (third edition, 2025) by François Chollet and Matthew Watson, plus legacy notebooks for earlier editions. The code is built on Keras 3 and can run with JAX, TensorFlow, or PyTorch backends, primarily on Google Colab.

## Use cases
- learn deep learning with python hands-on
- run keras 3 code examples with jax tensorflow or pytorch
- companion notebooks for deep learning with python book
- practice neural networks on colab free gpu
- study code samples from francois chollet's book
- learn keras and deep learning from scratch

## When to choose
- you are reading the book and want runnable code side by side
- you want to learn deep learning through executable Keras 3 notebooks
- you want free GPU-based examples that run on Colab's free tier

## When to avoid
- you want standalone tutorials with full explanatory text - the notebooks omit the book's prose and figures
- you need production-ready model code rather than educational samples
- you don't want to create a Kaggle account for chapters requiring Kaggle datasets

## Facets
- artifact type: learning-resource
- maturity: active
- function: machine-learning, deep-learning, llm-training
- domain: deep-learning, machine-learning, tutorials, education
- platform: python
- tags: jupyter-notebooks, keras, book-companion, tensorflow, pytorch, jax, gpu, web-server

## Member repositories
- fchollet/deep-learning-with-python-notebooks (main) score 51

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:11:29.864071+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 2026-08-29T16:59:02.851467+00:00, confidence not recorded.
  - readme: https://github.com/fchollet/deep-learning-with-python-notebooks (fetched 2026-08-28T04:11:29.864071+00:00, sha 52510f78019c)
- Data as of 2026-08-30T08:39:29.467469+00:00.