Introduction to
Machine Learning
Machine learning algorithms are used to make decisions in a wide variety of applications, including recommendation systems, criminal justice, healthcare, and more. This course explores several common machine learning algorithms: how they work, their strengths and limitations, their applications to real-world datasets, their implementation via Python frameworks, and the ethical and societal consequences of their use.
Staff
Instructor: Prof. Kim Mandery (she/her)
Email: mander1@stolaf.edu
Office: RMS 407
Office Hours: M 12-2pm (virtual, sign-up); T 2:30-3:30pm; W 10:30am-12:30pm, or by appt.
TA
TA: Brooke Barenz
Office Hours: Tuesdays and Thursdays 6-8pm
Drop-in lab: RNS 203
Additional help can often be found in the drop-in lab from Sunday-Thursdays around 6-8pm.
We will be using this site for most of our course content. Navigate to the schedule or course content using the wiki at the top of this page. You can read the syllabus here.
This site was made using Quarto! If you are interested in building your own site to host your portfolio, reach out to Prof. Kim and she’ll help you get started.