Machine Learning for the Quantified Self: On the Art of Learning from Sensory Data: 35 (Cognitive Systems Monographs, 35) - Tapa dura

Libro 22 de 31: Cognitive Systems Monographs

Funk, Burkhardt; Hoogendoorn, Mark

 
9783319663074: Machine Learning for the Quantified Self: On the Art of Learning from Sensory Data: 35 (Cognitive Systems Monographs, 35)
Tapa dura
ISBN 10: 3319663070 ISBN 13: 9783319663074
Editorial: Springer, 2017

Sinopsis

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 approaches allow this type of data to be analyzed. 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.

"Sinopsis" puede pertenecer a otra edición de este libro.

De la contraportada

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. 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 approaches allow this type of data to be analyzed. While there are sample 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.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
Springer
Año de publicación
2017
Idioma
Inglés
ISBN 10 
3319663070
ISBN 13 
9783319663074
Encuadernación
Tapa dura
Número de edición
1
Número de páginas
248
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Otras ediciones populares con el mismo título

9783319882154: Machine Learning for the Quantified Self: On the Art of Learning from Sensory Data: 35 (Cognitive Systems Monographs, 35)

Edición Destacada

ISBN 10:  3319882155 ISBN 13:  9783319882154
Editorial: Springer-Verlag GmbH, 2018
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