# shunliz/Machine-Learning

机器学习原理

Repository: https://github.com/shunliz/Machine-Learning
Canonical: https://ross.abutalabs.com/products/shunliz-machine-learning
Language: Python
License Family: other
Last push: 2025-08-03T02:04:52+00:00

## Health v2 (maintenance only)
Score: 48/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 34, release rhythm 35, longevity 100
- inputs: {"age_days": 3384, "days_push": 396, "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 1428, forks 304 (observed 2026-08-28T04:04:42.048384+00:00)

## What it is
A curated collection of study notes on machine learning principles, published as a Gitbook, covering mathematical foundations (calculus, probability, linear algebra) and machine learning/deep learning theory with detailed formula derivations. The latter half focuses on engineering practice, including Python ML libraries, feature engineering, and model evaluation.

## Use cases
- learn the math behind machine learning algorithms
- study gradient descent and convex optimization derivations
- understand MCMC and Gibbs sampling
- review feature engineering and dimensionality reduction techniques like PCA and SVD
- find notes on scikit-learn, TensorFlow, and Spark usage
- prepare for machine learning interviews

## When to choose
- you want free, comprehensive notes with detailed mathematical derivations
- you prefer reading structured theory alongside practical Python examples
- you can read Chinese-language technical material

## When to avoid
- you need a maintained software library or runnable codebase
- you want original, licensed content with clear attribution
- you need up-to-date coverage of modern LLM-era techniques

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: machine-learning, deep-learning, data-science, math
- domain: machine-learning, deep-learning, data-science, tutorials, mathematics
- platform: python, cross-platform
- tags: notes, gitbook, chinese-language, theory, math-foundations, study-guide

## Member repositories
- shunliz/Machine-Learning (main) score 48

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:42.048384+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 2026-08-30T04:37:19.849859+00:00, confidence not recorded.
  - readme: https://github.com/shunliz/Machine-Learning (fetched 2026-08-28T04:04:42.048384+00:00, sha e41d44325a40)
- Data as of 2026-08-30T08:39:29.467469+00:00.