CSCI 0451

Machine Learning

Machine Learning
Machine learning algorithms detect patterns in data and use these patterns to make decisions. This course introduces the theory and practice of machine learning. Tasks considered may include classification, regression, clustering, dimensionality reduction, text embedding, and reinforcement learning. Applications may include predictive analytics, data visualization, pattern recognition, and strategic game-playing. We will also discuss the social implications of automated decision systems. This course fulfills the Responsible Computing requirement for the Computer Science major. (Not open to students who have already taken CSCI 1051.) (CSCI 0200 and CSCI 0201 and MATH 0200) 3 hrs. lect./lab
Computer Science
Computer Science
Natural Sciences
Requirements Fulfilled:
Equivalent Courses:
CSCI 1051


Spring 2025

CSCI0451A-S25 Lecture

Spring 2024

CSCI0451A-S24 Lecture (Chodrow)

Spring 2023

CSCI0451A-S23 Lecture (Chodrow)
CSCI0451B-S23 Lecture (Chodrow)

Spring 2021

CSCI0451A-S21 Lecture (Foley)

Fall 2018

CSCI0451A-F18 Lecture (Scharstein)

Fall 2017

CSCI0451A-F17 Lecture (Scharstein)

Fall 2013

CSCI0451A-F13 Lecture (Kauchak)

Fall 2006

CSCI0451A-F06 Lecture (Huang)