# virgili0/Virgilio

Your new Mentor for Data Science E-Learning.

Repository: https://github.com/virgili0/Virgilio
Canonical: https://ross.abutalabs.com/products/virgilio
Homepage: https://virgili0.github.io/Virgilio/
Language: Jupyter Notebook
License: NOASSERTION
License Family: other
Topics: tensorflow, machine-learning, machine-vision, datascience, scikit-learn, python, guide, guidelines, path, study, studypath, learning, learning-python, computer-vision, nlp, statistics, business-intelligence, data-science, virgilio, hacktoberfest
Last push: 2025-10-14T17:32:44+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": 2731, "days_push": 323, "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 14966, forks 2505 (observed 2026-08-28T04:11:09.007030+00:00)

## What it is
Virgilio is an open-source e-learning initiative that provides curated guides and structured learning paths for Data Science, organized into three levels (Paradiso, Purgatorio, Inferno). It helps beginners and practitioners navigate the overwhelming amount of online Data Science resources for free.

## Use cases
- learn data science from scratch with a structured path
- find a beginner-friendly machine learning curriculum
- study python and statistics for data science
- learn computer vision and NLP fundamentals
- get guidance on starting a real data science project
- find curated resources instead of scattered tutorials

## When to choose
- you are self-learning data science and need a clear roadmap
- you want free, curated, community-maintained study guides
- you are a beginner overwhelmed by fragmented online tutorials

## When to avoid
- you need interactive courses with graded exercises or certificates
- you need up-to-date coverage of the newest tools and LLM-era practices
- you want production-ready code or a software library

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: machine-learning, data-science, nlp, computer-vision, documentation
- domain: data-science, machine-learning, tutorials, education
- platform: python
- tags: e-learning, study-path, guides, curated-resources, jupyter-notebook, web-server

## Member repositories
- virgili0/Virgilio (main) score 53

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:11:09.007030+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 2026-08-29T17:06:47.613362+00:00, confidence not recorded.
  - readme: https://github.com/virgili0/Virgilio (fetched 2026-08-28T04:11:09.007030+00:00, sha 248811d43166)
  - homepage: https://virgili0.github.io/Virgilio/ (fetched 2026-08-29T08:04:47.792161+00:00, sha 6c34cd3d495b)
- Data as of 2026-08-30T08:39:29.467469+00:00.