# gimseng/99-ML-Learning-Projects

A list of 99 machine learning projects for anyone interested to learn from coding and building projects

Repository: https://github.com/gimseng/99-ML-Learning-Projects
Canonical: https://ross.abutalabs.com/products/99-ml-learning-projects
Language: Jupyter Notebook
License: MIT
License Family: permissive
Topics: hacktoberfest
Last push: 2024-07-04T13:09:49+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2244, "days_push": 790, "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 1199, forks 233 (observed 2026-08-28T04:03:57.806391+00:00)

## What it is
A community-curated collection of 99 machine learning coding exercises and solutions, currently at 10 completed projects. Exercises range from beginner (linear regression, Titanic prediction) to advanced (LSTM text generation) and are contributed via issue tickets and reviewed pull requests.

## Use cases
- learn machine learning by building projects
- find beginner ML coding exercises
- practice implementing kNN from scratch
- get hands-on with sentiment analysis and LSTM text generation
- contribute ML exercises and solutions to open source
- find structured ML homework-style problems

## When to choose
- you learn best by coding exercises rather than reading theory
- you want graded difficulty from beginner to advanced ML projects
- you want to practice with Jupyter notebooks and scikit-learn
- you want an open-source project to contribute to during Hacktoberfest

## When to avoid
- you need production-ready ML code or libraries
- you expect all 99 projects to exist already (only 10 are complete)
- you need deep learning frameworks coverage beyond basic examples
- you want a structured course with lectures rather than exercises

## Facets
- artifact type: learning-resource
- maturity: active
- function: machine-learning, nlp, computer-vision, data-science
- domain: machine-learning, education, tutorials, computer-vision
- platform: python, cross-platform
- tags: jupyter-notebook, exercises, beginner-friendly, hacktoberfest, project-based-learning, sklearn, natural-language-processing

## Member repositories
- gimseng/99-ML-Learning-Projects (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:57.806391+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 2026-08-30T06:20:53.319511+00:00, confidence not recorded.
  - readme: https://github.com/gimseng/99-ML-Learning-Projects (fetched 2026-08-28T04:03:57.806391+00:00, sha 5a5f537ee1c0)
- Data as of 2026-08-30T08:39:29.467469+00:00.