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Machine Learning for the Quantified Self by Mark Hoogendoorn,... - 9783319663074
Machine Learning for the Quantified Self by Mark Hoogendoorn,... - 9783319663074
Machine Learning for the Quantified Self by Mark Hoogendoorn,... - 9783319663074
Machine Learning for the Quantified Self by Mark Hoogendoorn,... - 9783319663074
Machine Learning for the Quantified Self by Mark Hoogendoorn,... - 9783319663074
Machine Learning for the Quantified Self by Mark Hoogendoorn,... - 9783319663074
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Machine Learning for the Quantified Self by Mark Hoogendoorn,... - 9783319663074

Machine Learning for the Quantified SelfOn the Art of Learning from Sensory Data

Author(s): Mark Hoogendoorn, Burkhardt Funk

Format: Hardback

Publisher: Springer International Publishing AG, Switzerland

Imprint: Springer International Publishing AG

ISBN-13: 9783319663074, 978-3319663074

Synopsis

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. Luckily, in the domain of artificial intelligence there are techniques that can help out: machine-learning.

Price now:

£120.48
View Cheapest Offer £120.48

Machine Learning for the Quantified Self by Mark Hoogendoorn,... - 9783319663074

Machine Learning for the Quantified SelfOn the Art of Learning from Sensory Data

Author(s): Mark Hoogendoorn, Burkhardt Funk

Format: Hardback

Publisher: Springer International Publishing AG, Switzerland

Imprint: Springer International Publishing AG

ISBN-13: 9783319663074, 978-3319663074

Synopsis

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. Luckily, in the domain of artificial intelligence there are techniques that can help out: machine-learning.

Price now:

£120.48
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Machine Learning for the Quantified SelfOn the Art of Learning from Sensory Data

Author(s): Mark Hoogendoorn, Burkhardt Funk

Format: Hardback

Publisher: Springer International Publishing AG, Switzerland

Imprint: Springer International Publishing AG

ISBN-13: 9783319663074, 978-3319663074

Synopsis

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. Luckily, in the domain of artificial intelligence there are techniques that can help out: machine-learning.

Product Specifications

General

format

hardcover

Language

english

series

cognitive systems monographs

type

textbook

View Cheapest Offer £120.48

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