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Nov 23, 2024
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ITCS 3156 - Introduction to Machine Learning
Introduction to the machine learning pipeline of data collection, feature creation, algorithms, and evaluation for classification and regression based on the fundamental foundations on Linear Algebra, Probability Theory, and Optimization. The course covers basic concepts, such as training, validation, overfitting, and error rates in addition to commonly used machine learning algorithms, such as linear regression, perceptrons, naive Bayes, logistic regression, neural networks, dimensionality reduction, clustering, and reinforcement learning.
Credit Hours: (3)
Prerequisite(s): ITSC 2214 , STAT 2122 , and MATH 2164
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