# PacktPublishing/Deep-Learning-with-Keras

Code repository for Deep Learning with Keras published by Packt

Repository: https://github.com/PacktPublishing/Deep-Learning-with-Keras
Canonical: https://ross.abutalabs.com/products/deep-learning-with-keras
Language: Jupyter Notebook
License: MIT
License Family: permissive
Last push: 2026-04-22T08:56:36+00:00

## Health v2 (maintenance only)
Score: 67/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 78, release rhythm 35, longevity 100
- inputs: {"age_days": 3421, "days_push": 133, "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 1048, forks 698 (observed 2026-08-28T04:03:22.367701+00:00)

## What it is
The official companion code repository for the Packt book 'Deep Learning with Keras', containing Jupyter Notebook examples for each chapter. It covers supervised and unsupervised deep learning models including CNNs, autoencoders, RBMs, and LSTMs using Keras and TensorFlow.

## Use cases
- learn deep learning with keras from book examples
- example code for building convolutional neural networks
- understand lstm and recurrent networks with keras
- implement autoencoders and restricted boltzmann machines
- practice image classification and handwritten digit recognition
- follow along with a deep learning tutorial book

## When to choose
- you are reading the book and want its supporting code
- you want runnable Jupyter Notebook examples of classic deep learning models in Keras
- you are a beginner learning CNNs, RNNs, LSTMs, and autoencoders

## When to avoid
- you need a production-ready deep learning library or framework
- you need up-to-date code for modern TensorFlow 2.x / Keras 3 APIs
- you want comprehensive documentation rather than book chapter code

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: deep-learning, machine-learning, nlp, image-processing
- domain: deep-learning, machine-learning, tutorials, computer-vision
- platform: python
- tags: keras, tensorflow, jupyter-notebooks, book-companion, packt, educational-code, natural-language-processing

## Member repositories
- PacktPublishing/Deep-Learning-with-Keras (main) score 67

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:22.367701+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 2026-08-30T07:00:35.556734+00:00, confidence not recorded.
  - readme: https://github.com/PacktPublishing/Deep-Learning-with-Keras (fetched 2026-08-28T04:03:22.367701+00:00, sha 37ab4cb8b292)
- Data as of 2026-08-30T08:39:29.467469+00:00.