Mark Hoogendoorn’s Book Published: Machine Learning for the Quantified Self
Mark Hoogendoorn (Assistant Professor of Artificial Intelligence within the Computational Intelligence group of the Department of Computer Science at the VU Amsterdam), alongside Burkhardt Funk (Leuphana University Lüneburg), have written a book titled: “Machine Learning for the Quantified Self – On the Art of Learning from Sensory Data”, which has recently been published by Springer.
Self-tracking has become part of the modern lifestyle, and the amount of data generated by these devices is so overwhelming that it is difficult to obtain useful insights from it. This book explains the complete loop to effectively use self-tracking data for machine learning. While it focuses on self-tracking data, the techniques explained are also applicable to sensory data in general, making it useful for a wider audience. Discussing concepts drawn from state-of-the-art scientific literature, it illustrates the approaches using a case study of a rich self-tracking data set. While there are ample books that explain machine-learning techniques, self-tracking data comes with its own difficulties that require dedicated techniques such as learning over time and across users. More information about the book can be found HERE
The Institute for Advanced Study (IAS) and Data Science Center (DSC) of the University of Amsterdam (UvA) are joining forces in a new joint fellowship for (teams of) researchers interested in exploring the intersection of data science and other disciplines. The first fellow of the new program, Dr. Davide Ceolin, will start his fellowship at the IAS on June 17. Ceolin is currently affiliated with CWI.
Nanda Piersma, lecturer at the University of Applied Sciences (AUAS), has been appointed as a crown member of the Social and Economic Counsil (SER). This is the first time that a lecturer has been appointed as member of the SER. Nanda Piersma was approached because of her expertise in the field of digitisation.
The ADS Thesis Awards aim to promote excellence in Data Science and AI from students at BSc and Master level. The Awards are open to students from all Amsterdam-based knowledge institutes.