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Can I read Hardware-Aware Probabilistic Machine Learning Models : Learning, Inference and Use Cases on EtoBox?

Hardware-Aware Probabilistic Machine Learning Models : Learning, Inference and Use Cases by Laura Isabel Galindez Olascoaga,Wannes Meert,Marian Verhelst (auth.) is a nonfiction available to read on EtoBox.

What is Hardware-Aware Probabilistic Machine Learning Models : Learning, Inference and Use Cases about?

This book proposes probabilistic machine learning models that represent the hardware properties of the device hosting them. These models can be used to evaluate the impact that a specific device configuration may have on resource consumption and performance of the machine learning task, with the overarching goal of balancing the two optimally. The book first motivates extreme-edge computing in the context of the Internet of Things (IoT) paradigm. Then, it briefly reviews the steps involved in th

Who reads Hardware-Aware Probabilistic Machine Learning Models : Learning, Inference and Use Cases?

It is typically read by self-directed learners exploring a subject in depth.

Common subject areas: history, science, philosophy, social sciences.

Author
Laura Isabel Galindez Olascoaga,Wannes Meert,Marian Verhelst (auth.)
Publisher
Springer International Publishing AG
Published
2021
Language
EN
ISBN
9783030740436
Category
nonfiction
Subjects
Computer Science, Engineering, Stem
Updated
2026-03-25

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