gavinkhung/machine-learning-visualized
ML algorithms implemented and derived from first-principles in Jupyter Notebooks and NumPy
This resource helps machine learning students and practitioners understand how core machine learning algorithms work. It provides interactive Jupyter Notebooks that visually demonstrate the training process of algorithms, showing how they learn and converge to optimal solutions. It's ideal for anyone looking to gain deeper intuition into ML algorithm mechanics.
1,003 stars. Actively maintained with 1 commit in the last 30 days.
Use this if you are studying machine learning and want to see step-by-step visualizations of algorithms like neural networks, logistic regression, or K-means clustering in action.
Not ideal if you're looking for a library to implement machine learning models for production applications or a quick reference for API usage.
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1,003
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66
Language
TeX
License
MIT
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Last pushed
Mar 03, 2026
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