# hanmq/MachineLearning_Zhouzhihua_ProblemSets

Exercises answers to the book "machine-learning" written by Zhou Zhihua。周志华《机器学习》课后习题，个人解答。各算法都拿numpy和pandas实现了一遍

Repository: https://github.com/hanmq/MachineLearning_Zhouzhihua_ProblemSets
Canonical: https://ross.abutalabs.com/products/machinelearning_zhouzhihua_problemsets
Language: Python
License Family: other
Last push: 2022-10-02T09:41:21+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": 2921, "days_push": 1431, "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 1682, forks 435 (observed 2026-08-28T04:05:21.744094+00:00)

## What it is
A collection of personal solutions to the exercises in Zhou Zhihua's 'Machine Learning' textbook (the 'Watermelon Book'), with algorithms like logistic regression, decision trees, SVM, and AdaBoost implemented from scratch in NumPy and Pandas. It serves as a study companion rather than a usable software library.

## Use cases
- solutions to watermelon book exercises
- implement machine learning algorithms from scratch in numpy
- study companion for zhou zhihua machine learning textbook
- learn how decision trees and SVM work via manual implementation
- reference answers for machine learning course homework
- understand AdaBoost and naive bayes with simple python code

## When to choose
- you are studying Zhou Zhihua's Machine Learning textbook and want worked exercise answers
- you want to see classic ML algorithms implemented from scratch without frameworks
- you prefer Chinese-language explanations with LaTeX formulas

## When to avoid
- you need a production-ready machine learning library
- you want maintained, tested, or licensed code
- you need deep learning or modern LLM topics

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: machine-learning, nlp
- domain: machine-learning, education, tutorials
- platform: python
- tags: watermelon-book, zhou-zhihua, exercise-solutions, numpy, pandas, textbook-companion, chinese

## Member repositories
- hanmq/MachineLearning_Zhouzhihua_ProblemSets (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:21.744094+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 2026-08-30T03:41:21.942834+00:00, confidence not recorded.
  - readme: https://github.com/hanmq/MachineLearning_Zhouzhihua_ProblemSets (fetched 2026-08-28T04:05:21.744094+00:00, sha 4d8b6cf86625)
- Data as of 2026-08-30T08:39:29.467469+00:00.