# dair-ai/Mathematics-for-ML

🧮  A collection of resources to learn mathematics for machine learning

Repository: https://github.com/dair-ai/Mathematics-for-ML
Canonical: https://ross.abutalabs.com/products/mathematics-for-ml
License Family: other
Topics: ai, deep-learning, machine-learning, mathematics, ml
Last push: 2023-01-24T22:38:34+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 1565, "days_push": 1317, "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 6370, forks 728 (observed 2026-08-28T04:09:42.877763+00:00)

## What it is
A curated collection of books, papers, and video lectures for learning the mathematics behind machine learning and deep learning. It aggregates free resources covering linear algebra, calculus, probability, optimization, and Bayesian methods.

## Use cases
- learn math for machine learning
- find free books on linear algebra and calculus for ML
- review probability and statistics before studying deep learning
- resources to understand backpropagation math
- beginner-friendly math prerequisites for AI
- study matrix calculus for deep learning

## When to choose
- you want a curated starting point for ML math resources
- you prefer free online books and video lectures
- you need to refresh math fundamentals before learning ML

## When to avoid
- you need interactive exercises or a structured course with feedback
- you want a software tool or library rather than learning materials

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: documentation
- domain: machine-learning, mathematics, deep-learning, tutorials
- platform: cross-platform
- tags: curated-list, mathematics, machine-learning, awesome-list, education

## Member repositories
- dair-ai/Mathematics-for-ML (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:42.877763+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 2026-08-29T17:45:12.578919+00:00, confidence not recorded.
  - readme: https://github.com/dair-ai/Mathematics-for-ML (fetched 2026-08-28T04:09:42.877763+00:00, sha 23928d38c18a)
- Data as of 2026-08-30T08:39:29.467469+00:00.