# Shujian2015/FreeML

A List of Data Science/Machine Learning Resources (Mostly Free)

Repository: https://github.com/Shujian2015/FreeML
Canonical: https://ross.abutalabs.com/products/freeml
License Family: other
Topics: machine-learning, data-science, deep-learning, natural-language-processing
Last push: 2024-05-31T07:43:21+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": 3143, "days_push": 824, "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 1130, forks 511 (observed 2026-08-28T04:03:42.220961+00:00)

## What it is
A curated list of mostly free data science and machine learning learning resources, including courses, video lectures, and textbooks. It is organized as a learning path covering machine learning, NLP, deep learning, systems, analytics, and more.

## Use cases
- find free machine learning courses
- learn data science from scratch
- find deep learning video lectures
- get a one month study plan for ML
- find free NLP textbooks and courses
- prepare for data science interviews

## When to choose
- you want a curated, mostly free learning path for data science or ML
- you are a non-CS learner looking for accessible starting points
- you need pointers to well-known courses and textbooks

## When to avoid
- you need software or code, not learning materials
- you want an exhaustive, frequently updated awesome list
- you need resources with guaranteed maintenance or licensing

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: machine-learning, data-science, deep-learning, nlp
- domain: machine-learning, data-science, deep-learning, tutorials
- platform: cross-platform
- tags: awesome-list, free-resources, courses, textbooks, curated-list, natural-language-processing

## Member repositories
- Shujian2015/FreeML (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:42.220961+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 2026-08-30T06:38:05.643070+00:00, confidence not recorded.
  - readme: https://github.com/Shujian2015/FreeML (fetched 2026-08-28T04:03:42.220961+00:00, sha 9fe812140618)
- Data as of 2026-08-30T08:39:29.467469+00:00.