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Volume 3 describes how resource-aware machine learning methods and techniques are used to successfully solve real-world problems. The book provides numerous specific application examples: in health and medicine for risk modelling, diagnosis, and treatment selection for diseases in electronics, steel...

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Bibliographic Details
Other Authors: Morik, Katharina (Editor), Wietfeld, Christian (Editor), Rahnenführer, Jörg (Editor)
Format: Electronic Book Chapter
Language:English
Published: Berlin/Boston De Gruyter 2022
Series:De Gruyter STEM
Subjects:
Chemistry
Algorithms & data structures
Databases
Computer networking & communications
Artificial intelligence
Resource-Constrained
Data Analysis
Resource-Aware Machine Learning
Embedded Systems and Machine Learning
Big Data and Machine Learning
Artificial Intelligence
Highly Distributed Data
ML on Small devices Data mining for Ubiquitous System Software
Cyber-physical systems
Machine learning in high-energy physics
Machine learning for knowledge discovery
Online Access:DOAB: download the publication
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Summary:Volume 3 describes how resource-aware machine learning methods and techniques are used to successfully solve real-world problems. The book provides numerous specific application examples: in health and medicine for risk modelling, diagnosis, and treatment selection for diseases in electronics, steel production and milling for quality control during manufacturing processes in traffic, logistics for smart cities and for mobile communications.
Physical Description:1 electronic resource (470 p.)
ISBN:9783110785982
9783110785975
9783110786149
Access:Open Access

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