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Machine Learning for Robotics and Computer Vision
Online Resources
Note: As a TUM student, if you are planning to take the exam and get credits, you are encouraged to participate in current course iteration during the semester.
Summary
In this lecture, the students will be introduced into the most frequently used machine learning methods in computer vision and robotics applications. The major aim of the lecture is to obtain a broad overview of existing methods, and to understand their motivations and main ideas in the context of computer vision and pattern recognition.
Prerequisites
Linear Algebra, Calculus and Probability Theory are essential building blocks to this course.
Videos
Lecture recordings from 2013/14 can be found on YouTube.
Lecture Material
Lecture slides and exercise material are available from previous semesters, for example Winter Semester 2017
