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.

Course contents

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.

Course material

Lecture handouts/slides.

Teaching schedule

Lectures on Wednesdays & Fridays at 14–16.

Completion methods

Examination, assignments and group works.

More information in the Aalto University study guide.

You can get a digital badge after completing this course.