Machine learning for mobile and pervasive systems
Max amount of FITech students: 25
During this course, students will learn good practices for machine learning with noisy and inaccurate data.
Feature extraction/feature subset selection, handling high dimensional data, ANN + deep learning, probabilistic graphical models, topic models as well as unsupervised learning and clustering, anomaly detection and recommender systems.
Lectures on Wednesdays & Fridays at 14–16.
Examination, assignments and group works.
More information in the Aalto University study guide.
You can get a digital badge after completing this course.
Hakua koskevat kysymykset
Tekoäly ja koneoppiminen