Machine learning and data mining are closely related capabilities that enable computers to learn to perform tasks without explicit programming, as well as discover interesting information from data. This course explores topics within machine learning and data mining, including classification, unsupervised learning, and association rule mining. Students will gain hands-on practice with popular machine learning and data mining algorithms, as well as discuss challenges, issues and solutions to working with complexities in real-world data.
|Class:||MWF 1:30-2:20 PM||Classroom:||King 327|
|Instructor:||Adam Eck||Email:||adam.eck [AT] oberlin.edu|
|Office:||King 223D||Office Hours:||T 9:30-11:00 AM (King 223D)
W 2:30-3:30 PM (King 223D)
F 4:00-5:00 PM (The Local)