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Название: Machine Learning for the Quantified Self: On the Art of Learning from Sensory Data
Автор: Mark Hoogendoorn, Burkhardt Funk
Издательство: Springer
Год: 2017
Страниц: 231
Формат: PDF, EPUB
Размер: 17 Mb
Язык: English
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 from state-of-the-art scientific literature, it illustrates the approaches using a case study of a rich self-tracking data set. 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.