PritK99/ML-Toolbox
Ancient Secrets of Machine Learning (Work in Progress)
This is a learning-focused collection of machine learning algorithms designed to help understand the theoretical underpinnings of various ML techniques. It provides examples of how different algorithms, such as Perceptrons or the Apriori Algorithm, are applied to datasets for tasks like predicting survival or finding correlated items. Data scientists, machine learning engineers, and students learning ML concepts would use this to deepen their understanding of how these tools work.
Use this if you are a data scientist or ML engineer looking to understand the core theory and implementation details of machine learning algorithms.
Not ideal if you need a production-ready library for deploying machine learning models, as this project focuses on theoretical understanding and practical examples rather than robust, scalable implementations.
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Last pushed
Feb 12, 2026
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