# mGalarnyk/Python_Tutorials

Python tutorials in both Jupyter Notebook and youtube format.

Repository: https://github.com/mGalarnyk/Python_Tutorials
Canonical: https://ross.abutalabs.com/products/python_tutorials
Homepage: https://medium.com/@GalarnykMichael
Language: Jupyter Notebook
License: MIT
License Family: permissive
Last push: 2026-08-25T07:24:40+00:00

## Health v2 (maintenance only)
Score: 77/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 99, release rhythm 35, longevity 100
- inputs: {"age_days": 3906, "days_push": 8, "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 1264, forks 1140 (observed 2026-08-28T04:04:10.523959+00:00)

## What it is
A collection of Python, machine learning, and AI tutorials provided as Jupyter Notebooks with companion blog posts and YouTube videos. It covers Python basics, APIs, and ML topics like random forests with scikit-learn.

## Use cases
- learn python basics from scratch
- jupyter notebook tutorials for machine learning
- how to use twitter api with python
- understand random forest with scikit-learn
- beginner python exercises with videos
- learn data science in python

## When to choose
- you prefer learning via notebooks paired with video walkthroughs
- you are a beginner wanting structured Python fundamentals
- you want free tutorials covering APIs and common ML algorithms

## When to avoid
- you need production-ready code or a maintained library
- you want a single coherent course rather than standalone tutorials
- you need deep, advanced coverage of specialized ML topics

## Facets
- artifact type: learning-resource
- maturity: active
- function: machine-learning, data-science, nlp, developer-tools
- domain: tutorials, machine-learning, data-science, education, programming-languages
- platform: python, cross-platform
- tags: jupyter-notebooks, python-basics, youtube-tutorials, apis, scikit-learn, beginner-friendly

## Member repositories
- mGalarnyk/Python_Tutorials (main) score 77

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:10.523959+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 2026-08-30T05:04:03.347152+00:00, confidence not recorded.
  - readme: https://github.com/mGalarnyk/Python_Tutorials (fetched 2026-08-28T04:04:10.523959+00:00, sha 3f7e4985b29c)
  - homepage: https://medium.com/@GalarnykMichael (fetched 2026-08-29T12:16:20.061210+00:00, sha a7f9db3281cc)
- Data as of 2026-08-30T08:39:29.467469+00:00.