PritK99/ML-Toolbox

Ancient Secrets of Machine Learning (Work in Progress)

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/ 100
Experimental

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.

machine-learning-education data-science-fundamentals algorithm-theory predictive-modeling-concepts
No License No Package No Dependents
Maintenance 10 / 25
Adoption 5 / 25
Maturity 8 / 25
Community 0 / 25

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Last pushed

Feb 12, 2026

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