# zslucky/awesome-AI-books

Some awesome AI related books and pdfs for learning and downloading, also apply some playground models for learning

Repository: https://github.com/zslucky/awesome-AI-books
Canonical: https://ross.abutalabs.com/products/awesome-ai-books
Language: Jupyter Notebook
License: MIT
License Family: permissive
Topics: books, pdf, ai, artificial-intelligence, machine-learning, deep-learning, mathematics, data-mining, algorithms, playground, reading, learning, reinforcement-learning, quantum-computing, quantum-algorithms, quantum-information
Last push: 2026-07-07T00:40:24+00:00

## Health v2 (maintenance only)
Score: 73/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 91, release rhythm 35, longevity 100
- inputs: {"age_days": 3111, "days_push": 58, "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 1797, forks 396 (observed 2026-08-28T04:05:37.629667+00:00)

## What it is
A curated awesome-list of AI-related books and PDFs for learning, covering machine learning, deep learning, mathematics, data mining, reinforcement learning, and quantum computing, with links to research organizations and training grounds. PDFs are hosted externally on Yandex.Disk due to GitHub storage limits.

## Use cases
- find free AI and machine learning books to download
- learning resources for deep learning and mathematics
- quantum computing and quantum AI reading material
- curated list of AI research papers and publications
- beginner-friendly AI textbooks in pdf format
- reinforcement learning and NLP study references

## When to choose
- you want a curated collection of AI learning books and PDFs
- you need structured reading material across AI subfields including quantum computing
- you are self-studying AI and want links to research organizations and playgrounds

## When to avoid
- you need runnable code or a software library rather than reading material
- you require commercially licensed content - the repo is for learning only
- you need files hosted directly on GitHub - PDFs are on external storage

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: documentation, developer-tools
- domain: artificial-intelligence, machine-learning, deep-learning, tutorials, awesome-lists
- platform: cross-platform
- tags: awesome-list, books, pdf, quantum-computing, reinforcement-learning, mathematics, data-mining, self-learning

## Member repositories
- zslucky/awesome-AI-books (main) score 73

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:37.629667+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 2026-08-30T03:22:47.224399+00:00, confidence not recorded.
  - readme: https://github.com/zslucky/awesome-AI-books (fetched 2026-08-28T04:05:37.629667+00:00, sha e173bd57640a)
- Data as of 2026-08-30T08:39:29.467469+00:00.