Machine Learning for the Quantified Self

Name: Machine Learning for the Quantified Self
Brand: Springer International Publishing AG
SKU: 9783319882154
Price: 178.73 EUR
Availability: InStock

On the Art of Learning from Sensory Data

Автор: Mark Hoogendoorn, Burkhardt Funk

Език:

Корици: С меки корици

Издател: Springer International Publishing AG

Наличност: Външен склад

Изпращаме след 5-8 дни

178.73 € 349.56 лв

This book explains the complete loop to effectively use self-tracking data for machine learning. Whi...

Информация за книгата

Автор

Mark Hoogendoorn, Burkhardt Funk

Език

Английски език

Корици

Книга - С меки корици

Издадена

2018

страници

231

EAN

9783319882154

Enbook ID

21376048

Издател

Springer International Publishing AG

Теглоt

385

Размери

155 x 235 x 14

Пълно описание

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.

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Machine Learning for the Quantified Self

On the Art of Learning from Sensory Data

Информация за книгата

Пълно описание

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Клиенти, които купиха тази книга, купиха също