Carte Machine Learning for the Quantified Self Mark Hoogendoorn

Machine Learning for the Quantified Self

On the Art of Learning from Sensory Data

Limbă: engleză
Legare: Copertă tare
Disponibilitate: În depozitul extern
Expediem în 10-13 zile
939.26 lei
This book explains the complete loop to effectively use self-tracking data for machine learning. Whi...

Informații despre carte

Limbă
engleză
Legare
Carte - Copertă tare
Publicat
2017
Pagini
231
EAN
9783319663074
ISBN
3319663070
Enbook ID
16803690
Greutate
526
Dimensiuni
245 x 165 x 20

Descriere completă

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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