# Niraj-Lunavat/Artificial-Intelligence

Awesome AI Learning with +100 AI Cheat-Sheets, Free online Books, Top Courses, Best Videos and Lectures, Papers, Tutorials, +99 Researchers, Premium Websites, +121 Datasets, Conferences, Frameworks, Tools

Repository: https://github.com/Niraj-Lunavat/Artificial-Intelligence
Canonical: https://ross.abutalabs.com/products/artificial-intelligence
Homepage: https://t.me/Artificial_intelligence_in
License Family: other
Last push: 2023-04-20T05:11:52+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": 2711, "days_push": 1231, "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 1864, forks 552 (observed 2026-08-28T04:05:46.046374+00:00)

## What it is
A curated awesome-list of artificial intelligence learning resources, including 100+ cheat-sheets, free online books, courses, videos, papers, tutorials, datasets, and tools. It serves as a reference index for learners in AI, machine learning, deep learning, and data science.

## Use cases
- find free AI and machine learning books
- machine learning cheat sheets for quick reference
- best courses to learn deep learning
- where to find datasets for AI projects
- learn data science from scratch resources
- AI research papers and tutorials collection

## When to choose
- you want a single curated index of AI learning materials
- you need cheat-sheets across ML, deep learning, Python, R, and math
- you are looking for free courses, books, and datasets in one place

## When to avoid
- you need runnable software or code libraries rather than links
- you want up-to-date resources - the list was last updated in 2023
- you need structured, searchable course content instead of a link collection

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: documentation, developer-tools
- domain: artificial-intelligence, machine-learning, deep-learning, data-science, tutorials, awesome-lists
- platform: cross-platform
- tags: cheat-sheets, awesome-list, curated-resources, datasets, courses, free-books

## Member repositories
- Niraj-Lunavat/Artificial-Intelligence (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:46.046374+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 2026-08-30T03:15:35.894481+00:00, confidence not recorded.
  - readme: https://github.com/Niraj-Lunavat/Artificial-Intelligence (fetched 2026-08-28T04:05:46.046374+00:00, sha 93cb5829a1c8)
  - homepage: https://t.me/Artificial_intelligence_in (fetched 2026-08-29T10:54:51.608285+00:00, sha 2c93af761926)
- Data as of 2026-08-30T08:39:29.467469+00:00.