jadijadi/machine_learning_with_python_jadi resource
The notebooks we use on ML course observed · 2026-08-28
Health v2 · maintenance only
53/100
- Activity 47
- Release rhythm 35
- Longevity 100
Flags: no_releases no_license
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 1808
- days_rel: n/a
- days_push: 321
- n_releases_24m: 0
Adoption not part of the score
1173 stars · 399 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
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
learning-resource · maturity active
machine-learning data-science machine-learning education data-science python jupyter-notebooks course-materials tutorial persian
1 source
- readme: https://github.com/jadijadi/machine_learning_with_python_jadi · fetched 2026-08-28 · 05d2bfeeadbc
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| jadijadi/machine_learning_with_python_jadi | main | 53 |
For agents
markdown · JSON · MCP: product_card(name="jadijadi/machine_learning_with_python_jadi")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem