Könyv Machine Learning for the Quantified Self Mark Hoogendoorn

Machine Learning for the Quantified Self

On the Art of Learning from Sensory Data

Nyelv: Angol
Kötés: Kemény kötésű
Elérhetőség: Beszállítói készleten
Küldés 10-13 napon belül
64 923 Ft
This book explains the complete loop to effectively use self-tracking data for machine learning. Whi...

Információk a könyvről

Nyelv
Angol
Kötés
Könyv - Kemény kötésű
Kiadva
2017
oldal
231
EAN
9783319663074
ISBN
3319663070
Enbook ID
16803690
Súly
526
Méretek
245 x 165 x 20

Teljes leírás

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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