What’s Hot: Machine Learning for the Quantified Self: On the Art of Learning from Sensory Data

Burkhardt Funk

Professorship for Information Systems, in particular Data Science

Nowadays, an ever increasing number of sensors surround us that collect information about our behavior and activities. Devices that embed these sensors include smartphones, smartwatches, and other types of personal devices we wear or carry with us. Machine learning techniques are an obvious choice to identifying useful patterns from this rich source of data. Here, we briefly describe the challenges that occur when processing this type of data and discuss what might be promising avenues for future work. This paper draws inspiration from a book we have recently written that will be published by Springer, 2017-11-20, 231 pages.

References

Title	What’s Hot: Machine Learning for the Quantified Self: On the Art of Learning from Sensory Data
Degree of recognition	International
Media name/outlet	Blog
Media type	Web
Country/Territory	Germany
Date	28.09.17
Producer/Author	Mark Hoogendoorn, Burkhardt Funk
URL	ii.tudelft.nl/bnvki/?p=1092
Persons	Burkhardt Funk

Description

Nowadays, an ever increasing number of sensors surround us that collect information about our behavior and activities. Devices that embed these sensors include smartphones, smartwatches, and other types of personal devices we wear or carry with us. Machine learning techniques are an obvious choice to identifying useful patterns from this rich source of data. Here, we briefly describe the challenges that occur when processing this type of data and discuss what might be promising avenues for future work. This paper draws inspiration from a book we have recently written that will be published by Springer, 2017-11-20, 231 pages.

Period	28.09.2017