chrinide/advanced-machine-learning

Machine Learning classifiers and examples from the graduate class at Stony Brook with Prof. Leman Akoglu. Adaboost, EM, HMM, KNN, Naive Bayes vs. Logistic Regression.

Advanced Machine Learning

This folder contain many algorithms that I wrote for the graduate Machine Learning class at Stony Brook University.

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Algorithms:

• Naive Bayes vs. Logistic Regression

• Adaboost

• kNN vs. SVM

• Expectation Maximization

• 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.

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Installation

$ pip install -r requirements.txt

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License

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