# rhiever/Data-Analysis-and-Machine-Learning-Projects

Repository of teaching materials, code, and data for my data analysis and machine learning projects.

Repository: https://github.com/rhiever/Data-Analysis-and-Machine-Learning-Projects
Canonical: https://ross.abutalabs.com/products/data-analysis-and-machine-learning-projects
Homepage: http://www.randalolson.com/blog/
Language: Jupyter Notebook
License Family: other
Topics: machine-learning, python, data-analysis, data-science, ipython-notebook, evolutionary-algorithm
Last push: 2023-06-21T09:06:28+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": 4220, "days_push": 1169, "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 6747, forks 2106 (observed 2026-08-28T04:09:48.273103+00:00)

## What it is
A collection of teaching materials, code, and datasets accompanying Randal S. Olson's data analysis and machine learning blog posts, primarily in Jupyter Notebook format. It includes worked examples such as path optimization with genetic algorithms and machine learning tutorials.

## Use cases
- learn machine learning with python through worked examples
- find example jupyter notebooks for data analysis
- study how to solve the traveling salesman problem with a genetic algorithm
- teaching materials for an intro data science course
- see end-to-end data analysis workflows on real datasets

## When to choose
- you want tutorial-style notebooks explaining data science and ML concepts
- you need example datasets and analyses for learning or teaching
- you want to follow along with Randy Olson's blog posts

## When to avoid
- you need a production-ready machine learning library or maintained tool
- you require an actively updated codebase with a clear license for all code
- you need support for modern Python versions out of the box

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: data-science, machine-learning, data-visualization
- domain: data-science, machine-learning, tutorials, data-visualization
- platform: python, cross-platform
- tags: jupyter-notebooks, teaching-materials, example-projects, evolutionary-algorithms, blog-companion

## Member repositories
- rhiever/Data-Analysis-and-Machine-Learning-Projects (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:48.273103+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 2026-08-29T17:42:35.807641+00:00, confidence not recorded.
  - readme: https://github.com/rhiever/Data-Analysis-and-Machine-Learning-Projects (fetched 2026-08-28T04:09:48.273103+00:00, sha c9207a338114)
  - homepage: http://www.randalolson.com/blog/ (fetched 2026-08-29T08:38:40.710781+00:00, sha 358c88d8ae9e)
  - site_page: https://www.randalolson.com/ (fetched 2026-08-29T08:38:40.720054+00:00, sha 1035db42c672)
- Data as of 2026-08-30T08:39:29.467469+00:00.