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 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.
On the 22nd of September LAB42 will host its Grand Opening from 15:00 onwards. LAB42 is an international hub for developing talent in the fields of digital innovation and AI. The building is the result of a partnership between the UvA, the municipality of Amsterdam and the business sector.
The UvA Data Science Centre, part of the University Library, is pleased to host its second yearly Data Science Day on the 13th of October 2022.