[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
Github Repo
gradient descent
minimization
cost function
linear regression
classification
Github Repo
classification
multi-class
logistic regression
gradient descent
support-vector-machines
Github Repo
support vector machine
matrix factorization
recommendation system
principal-components
Github Repo
principal component analysis
singular value decomposition
clustering
k-means