jayinai/ml-cheatsheet

A constantly updated python machine learning cheatsheet

40
/ 100
Emerging

This project provides a practical guide and reusable code snippets for anyone building machine learning models from scratch. It walks you through a typical machine learning workflow, showing you how to prepare raw data, explore its characteristics, and engineer relevant features. The target user is a data scientist or data analyst who needs to develop a predictive model from structured datasets.

167 stars. No commits in the last 6 months.

Use this if you are a data scientist or analyst looking for a structured approach and common code patterns to clean data, understand its distributions, and prepare it for machine learning algorithms.

Not ideal if you are looking for advanced machine learning model training and deployment strategies, or if your primary focus is on unstructured data types like images or text.

data-science data-analysis machine-learning-workflow exploratory-data-analysis feature-engineering
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 8 / 25
Community 22 / 25

How are scores calculated?

Stars

167

Forks

53

Language

License

Last pushed

Aug 24, 2017

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/jayinai/ml-cheatsheet"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.