Home Machine Learning for the Quantified Self: On the Art of Learning from Sensory Data by Mark Hoogendoorn; Burkhardt Funk (ISBN: 9783319663074)

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Machine Learning for the Quantified Self: On the Art of Learning from Sensory Data Hardback - 2017

Name: Machine Learning for the Quantified Self : On the Art of Learning from Sensory Data
Price: 147.81 GBP
Availability: InStock
Author: Mark Hoogendoorn
ISBN: 9783319663074

by Mark Hoogendoorn; Burkhardt Funk

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From the publisher

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.

From the rear cover

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.

Details

Title Machine Learning for the Quantified Self: On the Art of Learning from Sensory Data
Author Mark Hoogendoorn; Burkhardt Funk
Binding Hardback
Pages 231
Volumes 1
Language ENG
Publisher Springer
Publication date 2017-10-05
Illustrated Yes
Features Illustrated
ISBN 9783319663074 / 3319663070
Weight 1.16 lbs (0.53 kg)
Dimensions 9.21 x 6.14 x 0.63 in (23.39 x 15.60 x 1.60 cm)
Category Computers - General Information
Dewey Decimal Code 006.3

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Machine Learning for the Quantified Self : On the Art of Learning from Sensory Data

by Mark Hoogendoorn

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ISBN 10 / ISBN 13: 9783319663074 / 3319663070
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Hardcover. New. New Book; Fast Shipping from UK; Not signed; Not First Edition; 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 wid