galafis/Customer-Segmentation-Analysis
Análise de Segmentação de Clientes usando Machine Learning.
What's novel
Análise de Segmentação de Clientes usando Machine Learning.
Code Analysis
9 files read · 3 roundsGenerates 200 rows of random uniform data, applies K-Means clustering (5 clusters) on two features, saves CSVs and two matplotlib plots, and displays a static HTML documentation page.
Strengths
The code is clean and readable for its scope, and the tests cover the basic functionality including output file verification and reproducibility with fixed seeds.
Weaknesses
The README massively overstates the project (claims 2,368 lines/9 modules/production-grade/CI-CD when it's ~80 lines in one file with no CI), the data is purely random with no real structure, the example file is entirely commented out, and the Dockerfile exposes a port but runs a one-shot script with no server.
Score Breakdown
Signal breakdown
Innovation
Craft
Traction
Scope
Evidence
Commits
20
Contributors
2
Files
17
Active weeks
5
Repository
Language
Python
Stars
1
Forks
0
License
MIT