TY - GEN

T1 - What’s Hot: Machine Learning for the Quantified Self

T2 - On the Art of Learning from Sensory Data

AU - Hoogendoorn, Mark

AU - Funk, Burkhardt

PY - 2017/9/28

Y1 - 2017/9/28

N2 - 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.

AB - 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.

KW - Informatik

KW - Wirtschaftsinformatik

UR - http://ii.tudelft.nl/bnvki/?p=1092

M3 - Wissenschaftliche Beiträge in Foren oder Weblogs

T3 - BNVKI.org

ER -