Machine learning for mobile and pervasive systems
During this course, students will learn good practices for machine learning with noisy and inaccurate data.
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.
