# exacity/simplified-deeplearning

Simplified implementations of deep learning related works

Repository: https://github.com/exacity/simplified-deeplearning
Canonical: https://ross.abutalabs.com/products/simplified-deeplearning
Language: Jupyter Notebook
License Family: other
Last push: 2024-11-02T08:23:25+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 3708, "days_push": 669, "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 2538, forks 808 (observed 2026-08-28T04:06:59.253752+00:00)

## What it is
A collection of Chinese-language study notes accompanying the Deep Learning Book, with simplified PyTorch and TensorFlow implementations of key concepts. It covers math foundations, CNNs, RNNs, autoencoders, and GANs through Jupyter Notebook examples.

## Use cases
- learn deep learning fundamentals from the Deep Learning Book
- find simple PyTorch implementations of CNN models like ResNet and GoogLeNet
- understand LSTM and RNN with example code
- study GANs and autoencoders with minimal implementations
- review linear algebra and probability for machine learning
- learn TensorFlow basics through worked examples

## When to choose
- you want concise, readable implementations of deep learning concepts alongside book-style explanations
- you prefer Chinese-language learning materials
- you are studying the Deep Learning Book and want companion code

## When to avoid
- you need production-ready or well-maintained deep learning libraries
- you require an English-language resource
- you need up-to-date coverage of modern architectures like transformers

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: deep-learning, machine-learning, data-science
- domain: deep-learning, machine-learning, tutorials, computer-vision
- platform: python, cross-platform
- tags: jupyter-notebook, pytorch, tensorflow, chinese, study-notes, deeplearningbook, gan, cnn, rnn, natural-language-processing

## Member repositories
- exacity/simplified-deeplearning (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:59.253752+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 2026-08-30T02:25:11.189185+00:00, confidence not recorded.
  - readme: https://github.com/exacity/simplified-deeplearning (fetched 2026-08-28T04:06:59.253752+00:00, sha 54a572f3716d)
- Data as of 2026-08-30T08:39:29.467469+00:00.