Machine learning for mobile and pervasive systems

Individual course

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.

Responsible teacher

Aalto University
Stephan Sigg
stephan.sigg(at)aalto.fi

Contact person for applications

FITech-verkostoyliopisto
Fanny Qvickström, Opintoasioiden suunnittelija
info(at)fitech.io

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