# Borye/machine-learning-coursera-1

This repo is specially created for all the work done my me as a part of Coursera's Machine Learning Course.

Repository: https://github.com/Borye/machine-learning-coursera-1
Canonical: https://ross.abutalabs.com/products/machine-learning-coursera-1
Language: MATLAB
License: MIT
License Family: permissive
Last push: 2019-07-28T13:49:39+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": 4388, "days_push": 2593, "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 1115, forks 888 (observed 2026-08-28T04:03:38.449080+00:00)

## What it is
A repository of completed coursework, assignments, and notes from Coursera's Machine Learning course by Andrew Ng. It serves as a reference for learners working through the same course.

## Use cases
- find solutions for coursera machine learning assignments
- study andrew ng's machine learning course materials
- reference matlab implementations of machine learning algorithms
- check my answers for ml course programming exercises
- learn machine learning fundamentals with worked examples

## When to choose
- you are taking the Coursera Machine Learning course and want reference solutions
- you prefer seeing worked MATLAB/Octave implementations of classic ML algorithms

## When to avoid
- you need a production machine learning library or framework
- you want modern deep learning content rather than the classic course
- you want to avoid spoilers and complete assignments independently

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: machine-learning
- domain: machine-learning, education, tutorials
- platform: python, cross-platform
- tags: coursera, andrew-ng, matlab, octave, course-assignments, study-notes

## Member repositories
- Borye/machine-learning-coursera-1 (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:38.449080+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 2026-08-30T06:42:08.388986+00:00, confidence not recorded.
  - readme: https://github.com/Borye/machine-learning-coursera-1 (fetched 2026-08-28T04:03:38.449080+00:00, sha 010ae62c0d0b)
- Data as of 2026-08-30T08:39:29.467469+00:00.