himanshu231204/ml-mastery
A structured Machine Learning learning & revision repository with hands-on notebooks, practical examples, and quick reference guides for developers and students.
This collection of notebooks helps you learn and revise machine learning concepts, bridging the gap between theoretical understanding and practical implementation. You'll go from raw data and mathematical explanations to working Python code and real-world project solutions. This is ideal for students, engineers, and anyone preparing for technical interviews who wants a complete reference for machine learning.
Use this if you need a comprehensive, structured guide to understand machine learning algorithms, their underlying math, and how to implement them from scratch and with production-ready libraries.
Not ideal if you're looking for an immediate plug-and-play solution for a specific business problem without needing to understand the technical details.
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8
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1
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Mar 22, 2026
Commits (30d)
0
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