Machine Learning and Pervasive Computing (Winter 2014/2015): Difference between revisions
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** [[Media:MLPC_01.pdf | Introduction (pdf)]] | ** [[Media:MLPC_01.pdf | Introduction (pdf)]] | ||
* Wednesday, '''October 29th, 2014, 10.15 - 11.45''': Lecture 2 | * Wednesday, '''October 29th, 2014, 10.15 - 11.45''': Lecture 2 | ||
** [[Media:MLPC_02.pdf | Classification and Evaluation (pdf)]] | |||
* Wednesday, '''November 5th, 2014, 10.15 - 11.45''': Lecture 3 | * Wednesday, '''November 5th, 2014, 10.15 - 11.45''': Lecture 3 | ||
* Wednesday, '''November 5th, 2014, 16.15 - 17.45''': Exercise 1 | * Wednesday, '''November 5th, 2014, 16.15 - 17.45''': Exercise 1 | ||
** [[Media:MLPC_Assignment_01.pdf | Assignment 1 (pdf)]] | |||
* Wednesday, '''November 12th, 2014, 10.15 - 11.45''': Lecture 4 | * Wednesday, '''November 12th, 2014, 10.15 - 11.45''': Lecture 4 | ||
* Wednesday, '''November 19th, 2014''': No lecture | * Wednesday, '''November 19th, 2014''': No lecture |
Revision as of 21:19, 29 October 2014
Details
Workload/ECTS Credits: | 180h, 5 ECTS |
Module: | M.Inf.1223: Spezielle fortgeschrittene Aspekte der Computernetzwerke |
Lecturer: | Stephan Sigg |
Teaching assistant: | -- |
Time: | Wednesdays, 10.15 - 11.45.; Exercise: 16:15 - 17:45 (bi-weekly) |
Place: | IfI 3.101 |
UniVZ | [1] |
Course Overview
The course will address selected topics in Pervasive Computing. This semester the main focus of the lecture will be on Machine learning and activity recognition from sensor-data. In addition, other fields of Pervasive Computing are covered to provide students with a good overview on current advances and research challenges. Depending on the interest of the students, the emphasis on these additional topics may differ.
- Course topics
- Introduction to Machine learning
- Supervised and Unsupervised learning
- Features and feature extraction
- Feature subset selection
- Performance metrics
- Polynomial curve fitting
- Support Vector Machines
- Artificial Neural Network learning
- Clustering (k-means)
- Dimensionality reduction
- Anomaly detection
- Recommender systems
Schedule
- Wednesday, October 22nd, 2014, 10.15 - 11.45: Lecture 1
- Wednesday, October 29th, 2014, 10.15 - 11.45: Lecture 2
- Wednesday, November 5th, 2014, 10.15 - 11.45: Lecture 3
- Wednesday, November 5th, 2014, 16.15 - 17.45: Exercise 1
- Wednesday, November 12th, 2014, 10.15 - 11.45: Lecture 4
- Wednesday, November 19th, 2014: No lecture
- Wednesday, November 26th, 2014, 10.15 - 11.45: Lecture 5
- Wednesday, November 26th, 2014, 16.15 - 17.45: Exercise 2
- Wednesday, December 3rd, 2014: No lecture
- Wednesday, December 10th, 2014, 10.15 - 11.45: Lecture 6
- Wednesday, December 17th, 2014, 10.15 - 11.45: Lecture 7
- Wednesday, December 17th, 2014, 16.15 - 17.45: Exercise 3
- Wednesday, January 7th, 2015, 10.15 - 11.45: Lecture 8
- Wednesday, January 14th, 2015, 10.15 - 11.45: Lecture 9
- Wednesday, January 14th, 2015, 16.15 - 17.45: Exercise 4
- Wednesday, January 21st, 2015, 10.15 - 11.45: Lecture 10
- Wednesday, January 28th, 2015, 10.15 - 11.45: Lecture 11
- Wednesday, January 28th, 2015, 16.15 - 17.45: Exercise 5
- Wednesday, February 4th, 2015, 10.15 - 11.45: Lecture 12
Requirements
- Each participant is required to attend and actively participate in the exercises.
- Oral examination at the end of the semester
Reading List
- Pervasive and Ubiquitous Computing
- Activity recognition