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

By (author) Mark Hoogendoorn, By (author) Burkhardt Funk

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normal price: R 3,713.95

Price: R 3,342.95

| book description |

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.

| product details |



Normally shipped | Available from overseas. Delivery time is 14 - 21 days
Publisher | Springer International Publishing AG
Published date | 15 Aug 2018
Language |
Format | Paperback / softback
Pages | 231
Dimensions | 235 x 155 x 0mm (L x W x H)
Weight | 0g
ISBN | 978-3-3198-8215-4
Readership Age |
BISAC | computers / artificial intelligence

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Normally shipped | Usually dispatched in 3 to 4 weeks as supplier is out of stock
Readership Age |
Normal Price | R 8,413.95
 Price | R 7,572.95 | on special |

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