lihanghang/ML
机器学习技术实践
This collection of machine learning code examples helps data scientists, analysts, and researchers understand and apply various algorithms. It takes real-world data like PM2.5 readings, company financials, or email content and demonstrates how to build models for tasks like predicting air quality, assessing credit risk, or detecting fraud. The output provides predictions, classifications, or generated data based on the trained models.
No commits in the last 6 months.
Use this if you are a data scientist or researcher looking for practical examples and experimental code to learn about or implement machine learning techniques across different domains and data types.
Not ideal if you need a production-ready application or a polished, fully documented library for immediate deployment, as this repository contains experimental and debug records.
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Last pushed
Sep 02, 2025
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