CMSC422 Introduction to Machine Learning - Spring 2026

Course Description

Machine Learning studies representations and algorithms that allow machines to improve their performance on a task from experience. This is a broad overview of existing methods for machine learning and an introduction to adaptive systems in general. Emphasis is given to practical aspects of machine learning and data mining.

Topics Covered

Decision Trees and Ensemble Learning
K-Nearest Neighbors
Perceptron and Convex Optimization
Linear Classifiers and Loss Functions
Naive Bayes and Logistic Regression
Neural Networks and Backpropagation
Convolutional Neural Networks (CNN)
K-Means Clustering
Principal Component Analysis (PCA) and Dimensionality Reduction
Support Vector Machines (SVM)
Recurrent Neural Networks (RNN) and LSTM
Introduction to Generative AI, Variational Autoencoders
Language Modeling and Transformers

Logistics

When & Where

Section 0301
Lecture: Tuesday and Thursday 12:30pm - 1:45pm · CSI 2117

Instructors

Furong Huang
Brendan Iribe Center for Computer Science and Engineering, Room 4124
furongh@umd.edu
https://furong-huang.com
Office hours: Tuesday and Thursday, 1:45 PM - 2:15 PM (after class), IRB 4124
Starting: February 17, 2026

Teaching Assistants

Minghui Liu (Ming)
minghui@umd.edu
Office hours: Wednesday 9am - 11am, AVW4140

Pankayaraj Pathmanathan (Pan)
pan@umd.edu
Office hours: Friday 1pm - 3pm, AVW4140

Contact Us

If you're a registered student, post questions on Piazza or send a message through ELMS. If not, send an email including "CMSC422" in the title.