Learn the theory, math and code behind different machine learning algorithms and techniques.
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Updated
Jul 8, 2022 - Python
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machine-learning-theory
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ML course project: investigation on common perceptions of same neural network model with different random seed
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May 31, 2020 - Python
This repository hosts a progressive series of implementations (Code_v1, Code_v2, and beyond) for deterministic β*-optimization in the Information Bottleneck framework. Includes symbolic fusion, multi-path inference, and Alpay Algebra–driven critical point validation (β* = 4.14144).
statistical-inference mutual-information machine-learning-theory phase-transition information-bottleneck symbolic-algebra alpay-algebra beta-optimization deep-theory ib-framework
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May 15, 2025 - Python
Implementation is to use gradient descent to find the optimal values of θ that minimize the cost function.
python data-science machine-learning optimization supervised-learning logistic-regression regularization gradient-descent predictive-modeling theta machine-learning-theory statistical-modeling cost-function mathematical-modeling
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Mar 1, 2025 - Python
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