Name	Name	Last commit message	Last commit date
parent directory ..
data	data
images	images
README.md	README.md
Topic1-Classification_Basics.ipynb	Topic1-Classification_Basics.ipynb
Topic2-Generalized_Linear_Models.ipynb	Topic2-Generalized_Linear_Models.ipynb
Topic3-Alternate_Classification_Models.ipynb	Topic3-Alternate_Classification_Models.ipynb
Topic4-High-dimensional_Classification.ipynb	Topic4-High-dimensional_Classification.ipynb

Name

Last commit message

Last commit date

Classification

Associated Notebooks:

Classification Basics - Intro to classification problems, accuracy metrics, multi-class classification and loss functions.
Generalized Linear Models - Perceptron, logistic regression, margin cost, and support vector machine model derivation and implementation.
Alternate Classification Models - Demonstrations of k-Nearest Neighbors, Naive Bayes, and decision trees.
High-dimensional Classification - Implementation of high-dimensional classification using the perovskite dataset.