# erhwenkuo/deep-learning-with-keras-notebooks

Jupyter notebooks for using & learning Keras

Repository: https://github.com/erhwenkuo/deep-learning-with-keras-notebooks
Canonical: https://ross.abutalabs.com/products/deep-learning-with-keras-notebooks
Language: Jupyter Notebook
License Family: other
Topics: deep-learning, keras-notebooks, keras
Last push: 2018-12-19T17:12:14+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": 3221, "days_push": 2814, "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 2196, forks 678 (observed 2026-08-28T04:06:25.179065+00:00)

## What it is
A collection of Jupyter notebooks documenting one developer's learning of Keras, covering CNNs, RNNs/LSTMs, autoencoders, seq2seq, image augmentation, and pretrained models. It serves as a hands-on tutorial resource for people getting started with deep learning using Keras and TensorFlow.

## Use cases
- learn keras with example notebooks
- deep learning tutorials for beginners
- image classification with pretrained models
- understand lstm and rnn basics
- build autoencoders in keras
- image augmentation for small datasets
- visualize what convnets learn

## When to choose
- you want hands-on, notebook-style examples for learning Keras
- you need beginner-friendly deep learning walkthroughs including Chinese-language explanations
- you want examples of CNNs, RNNs, autoencoders, and transfer learning

## When to avoid
- you need a maintained library or up-to-date Keras/TensorFlow APIs (last updated 2018)
- you need production code or a license permitting reuse
- you want modern frameworks like PyTorch or current Keras 3

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: deep-learning, machine-learning, image-processing, data-visualization
- domain: deep-learning, machine-learning, computer-vision, tutorials
- platform: python, windows, cross-platform
- tags: keras, jupyter-notebooks, tensorflow, cnn, rnn, lstm, autoencoder, image-classification, transfer-learning, chinese-language, natural-language-processing, gpu

## Member repositories
- erhwenkuo/deep-learning-with-keras-notebooks (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:25.179065+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 2026-08-30T02:47:13.326418+00:00, confidence not recorded.
  - readme: https://github.com/erhwenkuo/deep-learning-with-keras-notebooks (fetched 2026-08-28T04:06:25.179065+00:00, sha 6dc4b64495a2)
- Data as of 2026-08-30T08:39:29.467469+00:00.