Machine learning for mobile and pervasive systems

During this course, students will learn good practices for machine learning with noisy and inaccurate data.
Image for course subject

Schedule:

Teaching time:

Daytime

Location:

Espoo

Topic:

Information and communications technology

Form of learning:

Exam
On-campus

Provider:

Aalto University, FITech

Level:

Advanced

Credits:

5 By Aalto University (ECTS)

Fee:

Free of charge

Target group and prerequisites

Recommended: skilled in programming.

Course description

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.

Application deadline: 4.1.2022.

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