DT

Machine Learning

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[CSCI 416] Intro to Machine Learning

Fall 2021

This class serves as an introduction to the theory and practice of machine learning, focusing primarily on methods for classification and prediction. Topics include decision trees, artificial neural networks, support vector machines, kernel methods, ensemble methods, clustering methods, dimension reduction, performance evaluation, data preprocessing, and hyperparameter tuning.

gradient-descent

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gradient descent

minimization

cost function

linear regression

classification

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classification

multi-class

logistic regression

gradient descent

support-vector-machines

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support vector machine

matrix factorization

recommendation system

principal-components

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principal component analysis

singular value decomposition

clustering

k-means