# jadijadi/machine_learning_with_python_jadi

The notebooks we use on ML course

Repository: https://github.com/jadijadi/machine_learning_with_python_jadi
Canonical: https://ross.abutalabs.com/products/machine_learning_with_python_jadi
Language: Jupyter Notebook
License Family: other
Last push: 2025-10-16T23:09:23+00:00

## Health v2 (maintenance only)
Score: 53/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 47, release rhythm 35, longevity 100
- inputs: {"age_days": 1808, "days_push": 321, "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 1173, forks 399 (observed 2026-08-28T04:03:51.798528+00:00)

## What it is
A collection of Jupyter notebooks used in Jadi's Python machine learning course on Maktabkhooneh. It serves as free educational material covering ML concepts with hands-on Python examples.

## Use cases
- learn machine learning with python
- follow along a beginner ML course
- practice ML with jupyter notebooks
- study supervised and unsupervised learning examples
- find course exercises and datasets for ML

## When to choose
- you want free, notebook-based ML tutorials
- you are a beginner learning Python machine learning
- you want to follow a structured video course with matching code

## When to avoid
- you need production-ready ML code or a library
- you require a maintained software package with a license
- you need advanced or research-level ML material

## Facets
- artifact type: learning-resource
- maturity: active
- function: machine-learning, data-science
- domain: machine-learning, education, data-science
- platform: python
- tags: jupyter-notebooks, course-materials, tutorial, persian

## Member repositories
- jadijadi/machine_learning_with_python_jadi (main) score 53

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:51.798528+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 2026-08-30T06:28:22.849405+00:00, confidence not recorded.
  - readme: https://github.com/jadijadi/machine_learning_with_python_jadi (fetched 2026-08-28T04:03:51.798528+00:00, sha 05d2bfeeadbc)
- Data as of 2026-08-30T08:39:29.467469+00:00.