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

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.