Unsupervised Learning
University of Maryland Baltimore County
Unsupervised learning is a category of machine learning algorithms that use unlabeled data and no prior training. Many algorithms fall into this category. This class will cover the more popular ones of K-Means, DBSCAN and Hierarchical Clustering. The course ends with a capstone project.
About this Course
Unsupervised learning is a category of machine learning algorithms that use unlabeled data and no prior training. Many algorithms fall into this category. This class will cover the more popular ones of K-Means, DBSCAN and Hierarchical Clustering. These algorithms can cluster data into groups. Some algorithms allow the user to decide how many groups that form, while other algorithms decide for the user. The course has weekly coding labs and ends with a capstone project. This allows students to demonstrate their understanding of the algorithms.
What You'll Learn
- What unsupervised learning is.
- Uses for K-Means algorithm and how to code it in Python.
- Uses for DBSCAN algorithm and how to code it in Python.
- Uses for Hierarchical Clustering algorithm and how to code it in Python.
Prerequisites
- Students should have basic coding skills.
Instructors
Michael Scott Brown
Program Chair of the Software Engineering Master’s