# louisfb01/start-machine-learning

A complete guide to start and improve in machine learning (ML), artificial intelligence (AI) in 2026 without ANY background in the field and stay up-to-date with the latest news and state-of-the-art techniques!

Repository: https://github.com/louisfb01/start-machine-learning
Canonical: https://ross.abutalabs.com/products/start-machine-learning
Homepage: https://www.louisbouchard.ai/learnai/
License: MIT
License Family: permissive
Topics: machine-learning, deep-learning, youtube, neural-networks, artificial-intelligence, course, coursera, coursera-machine-learning, tutorial, tutorials, practice, cheat-sheets, read-articles, learning, learn-to-code, learning-python, linear-algebra, probability-statistics, youtube-playlist, data-science
Last push: 2026-01-23T19:51:33+00:00

## Health v2 (maintenance only)
Score: 61/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 63, release rhythm 35, longevity 100
- inputs: {"age_days": 2169, "days_push": 222, "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 5296, forks 698 (observed 2026-08-28T04:09:15.253088+00:00)

## What it is
A curated, free guide to learning machine learning and artificial intelligence from zero background, collecting courses, videos, books, articles, math and coding resources. It is maintained by Louis-François Bouchard (What's AI) and updated with state-of-the-art techniques and news.

## Use cases
- learn machine learning from scratch with no background
- find free AI and ML courses and tutorials
- build a study roadmap for becoming an ML engineer
- catch up on math needed for machine learning
- learn Python for AI as a non-developer
- stay up to date with state-of-the-art ML techniques

## When to choose
- you are a complete beginner wanting a structured, free path into ML/AI
- you want curated links to courses, books, videos, and practice resources in one place
- you need guidance on math and coding prerequisites for machine learning

## When to avoid
- you are an experienced ML practitioner looking for advanced research material
- you want an interactive course platform rather than a curated list of links
- you need hands-on tooling or code rather than learning resources

## Facets
- artifact type: learning-resource
- maturity: active
- function: documentation, developer-tools
- domain: machine-learning, artificial-intelligence, tutorials, data-science, education
- platform: -
- tags: curated-guide, roadmap, free-resources, beginner-friendly, youtube-playlists, cheat-sheets, self-learning, web-server

## Member repositories
- louisfb01/start-machine-learning (main) score 61

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:15.253088+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 2026-08-29T17:59:10.877724+00:00, confidence not recorded.
  - readme: https://github.com/louisfb01/start-machine-learning (fetched 2026-08-28T04:09:15.253088+00:00, sha 1ca2f2e71ae9)
  - homepage: https://www.louisbouchard.ai/learnai/ (fetched 2026-08-29T08:54:17.675169+00:00, sha c811eec9cb11)
  - site_page: https://www.louisbouchard.ai/about (fetched 2026-08-29T08:54:17.685932+00:00, sha ceadedd4d6c8)
  - site_page: https://www.louisbouchard.ai/faq (fetched 2026-08-29T08:54:17.687804+00:00, sha 435b053cfaa1)
- Data as of 2026-08-30T08:39:29.467469+00:00.