# veb-101/Data-Science-Projects

Collection of data science projects in Python

Repository: https://github.com/veb-101/Data-Science-Projects
Canonical: https://ross.abutalabs.com/products/data-science-projects
Language: Jupyter Notebook
License Family: other
Last push: 2023-11-11T19:46:32+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2309, "days_push": 1026, "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 2772, forks 646 (observed 2026-08-28T04:07:19.039361+00:00)

## What it is
A curated collection of data science projects implemented in Python via Jupyter Notebooks, intended for hands-on learning. It covers a range of topics from basic to advanced as a self-study resource.

## Use cases
- learn data science through hands-on projects
- find python project ideas for a portfolio
- practice machine learning with jupyter notebooks
- study example data science project implementations
- get project topics for self-study

## When to choose
- you want guided, notebook-based data science projects to learn from
- you need project ideas to build a data science portfolio
- you prefer learning by working through complete examples

## When to avoid
- you need production-ready, maintained software with a license
- you want a library or framework to depend on
- you need guaranteed updates or support

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: data-science, machine-learning, nlp, data-visualization
- domain: data-science, machine-learning, tutorials, education
- platform: python
- tags: jupyter-notebooks, hands-on-projects, learning-projects, portfolio-projects

## Member repositories
- veb-101/Data-Science-Projects (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:19.039361+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 2026-08-30T08:16:38.306625+00:00, confidence not recorded.
  - readme: https://github.com/veb-101/Data-Science-Projects (fetched 2026-08-28T04:07:19.039361+00:00, sha 2ed666279e56)
- Data as of 2026-08-30T08:39:29.467469+00:00.