Authors : Dr. Mitat Uysal

Volume/Issue : Volume 10 - 2025, Issue 5 - May

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Google Scholar : https://tinyurl.com/2j8jdsay

DOI : https://doi.org/10.38124/ijisrt/25may1735

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

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Abstract : Topological Machine Learning (TML) leverages tools from algebraic topology, especially persistent homology, to extract robust features from data that remain invariant under continuous deformations. This article presents a comprehensive overview of the theoretical underpinnings of TML, historical evolution, core equations, and a Python-based implementation of a topological handwritten digit classifier using artificial data. We avoid common libraries like sklearn and tensorflow, ensuring complete control and transparency of computation.

Keywords : Topological Machine Learning,Topology,Homology,Topological Features in ML,Topological Digit Classifier.

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