# atinesh/Coursera-Machine-Learning-Stanford

Machine learning-Stanford University

Repository: https://github.com/atinesh/Coursera-Machine-Learning-Stanford
Canonical: https://ross.abutalabs.com/products/coursera-machine-learning-stanford
Language: MATLAB
License Family: other
Topics: machine-learning, coursera, stanford-university
Last push: 2026-06-06T09:33:45+00:00

## Health v2 (maintenance only)
Score: 71/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 86, release rhythm 35, longevity 100
- inputs: {"age_days": 3714, "days_push": 88, "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 1180, forks 747 (observed 2026-08-28T04:03:53.588207+00:00)

## What it is
A collection of solutions to the programming assignments and quizzes of Andrew Ng's Machine Learning course on Coursera (Stanford University), written in MATLAB/Octave. It also includes lecture slides and serves as a study reference for learners stuck on assignments.

## Use cases
- solutions to coursera machine learning assignments
- study andrew ng machine learning course
- matlab octave machine learning examples
- reference for machine learning algorithms homework
- learn supervised learning regression and neural networks basics

## When to choose
- you are taking the Coursera Machine Learning course and get stuck on an assignment
- you want worked MATLAB/Octave examples of classic ML algorithms
- you want lecture slides and quiz solutions alongside code

## When to avoid
- you need a production machine learning library or framework
- you want to skip doing the assignments yourself and just copy answers
- you need modern Python-based ML tooling or deep learning code

## Facets
- artifact type: learning-resource
- maturity: stable
- function: machine-learning
- domain: machine-learning, education, tutorials
- platform: python, cross-platform
- tags: coursera, andrew-ng, matlab, octave, assignments, solutions, stanford

## Member repositories
- atinesh/Coursera-Machine-Learning-Stanford (main) score 71

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:53.588207+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 2026-08-30T06:25:15.981365+00:00, confidence not recorded.
  - readme: https://github.com/atinesh/Coursera-Machine-Learning-Stanford (fetched 2026-08-28T04:03:53.588207+00:00, sha d468a5df7e30)
- Data as of 2026-08-30T08:39:29.467469+00:00.