# Ma-Lab-Berkeley/deep-representation-learning-book

Learning Deep Representations of Data Distributions

Repository: https://github.com/Ma-Lab-Berkeley/deep-representation-learning-book
Canonical: https://ross.abutalabs.com/products/deep-representation-learning-book
Homepage: https://ma-lab-berkeley.github.io/deep-representation-learning-book/
Language: TeX
License Family: other
Last push: 2026-09-02T15:36:20+00:00

## Health v2 (maintenance only)
Score: 63/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 100, release rhythm 35, longevity 30
- inputs: {"age_days": 426, "days_push": 0, "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 1034, forks 113 (observed 2026-09-03T02:15:06.551416+00:00)

## What it is
Source repository for the open book 'Learning Deep Representations of Data Distributions', written in LaTeX with Python code that generates the book's figures. It lets readers build the book or individual chapters, run figure code, and contribute translations or content.

## Use cases
- learn deep representation learning from a free textbook
- build a deep learning book pdf from latex source
- run python code that generates book figures
- find a free book on deep representations of data distributions
- contribute translations to an open machine learning book

## When to choose
- you want a rigorous, freely available text on deep representation learning
- you want to rebuild the book or chapters yourself
- you want the code behind the book's figures

## When to avoid
- you just want to read the book - use the published PDF instead
- you need a software library or tool for training models
- you need a stable, licensed dependency for a project

## Facets
- artifact type: learning-resource
- maturity: active
- function: documentation, data-visualization, machine-learning
- domain: deep-learning, machine-learning, tutorials, education
- platform: python, cross-platform
- tags: latex-book, textbook, representation-learning, open-textbook, figure-code

## Member repositories
- Ma-Lab-Berkeley/deep-representation-learning-book (main) score 63

## Provenance
- Observed fields: from GitHub, fetched 2026-09-03T02:15:06.551416+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 2026-08-30T07:07:43.100833+00:00, confidence not recorded.
  - readme: https://github.com/Ma-Lab-Berkeley/deep-representation-learning-book (fetched 2026-09-03T02:15:06.551416+00:00, sha f7727241ad36)
  - homepage: https://ma-lab-berkeley.github.io/deep-representation-learning-book/ (fetched 2026-08-29T13:07:29.066378+00:00, sha 1d2d01efcfdb)
- Data as of 2026-08-30T08:39:29.467469+00:00.