Mohlo by se vám také líbit

Více informací o knize Machine Learning for the Quantified Self

• Parametry knihy
• Anotace
• Oblíbené z jiného soudku

Nákupem získáte 400 bodů

Anotace knihy

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.

Parametry knihy

Zařazení knihy Knihy v angličtině Computing & information technology Computer science Artificial intelligence

• Plný název: Machine Learning for the Quantified Self
• Podnázev: On the Art of Learning from Sensory Data
• Autor: Mark Hoogendoorn, Burkhardt Funk
• Jazyk: Angličtina
• Vazba: Pevná
• Počet stran: 231
• EAN: 9783319663074
• ISBN: 3319663070
• ID: 16803690
• Nakladatelství: Springer International Publishing AG
• Hmotnost: 526 g
• Rozměry: 165 × 245 × 20 mm
• Datum vydání: 05. October 2017

Oblíbené z jiného soudku

---

---

---