Introduction to Estimation and Machine Learning

Fall Semester 2022

Prof. Hans-Andrea Loeliger

Location: ETF C1, Zoom (meeting ID will be sent to the registered participants)
Lectures: Friday, 14:15-16:00
Tutorial sessions: ETF C1, Zoom (time slots & meeting IDs will be announced to the registered participants)
Assistants: Elizabeth Ren

Lecture Notes, Problems, and Solutions (login)

Description

  • probability and estimation
  • Hilbert spaces and linear learning
  • learning nonlinear functions
  • neural networks
  • kernel methods

Prerequisites

Standard first courses in linear algebra and probability theory.

Lecture Notes

Complete lecture notes (in English) will be handed out as the course progresses.

Examination

Written (in English).

 

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