This folder contain many algorithms that I wrote for the graduate Machine Learning class at Stony Brook University.
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Naive Bayes vs. Logistic Regression
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Adaboost
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kNN vs. SVM
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Expectation Maximization
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Hidden Markov Chain
It also contains the theory from mt homework. For the final project about classifying complex networks, please refer to the specific repository.
$ pip install -r requirements.txt
When making a reference to my work, please use my twitter handle b_t_3 or my website.
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License