From 5e096ed9ea17a08f9ad31c98595d90395a44f60a Mon Sep 17 00:00:00 2001 From: Vijay Janapa Reddi Date: Sat, 30 Sep 2023 10:36:25 -0400 Subject: [PATCH] Added an abstract --- _quarto.yml | 2 ++ 1 file changed, 2 insertions(+) diff --git a/_quarto.yml b/_quarto.yml index b33193c6..ce68324d 100644 --- a/_quarto.yml +++ b/_quarto.yml @@ -2,6 +2,8 @@ project: type: book output-dir: _book +abstract: Machine Learning Systems for tinyML offers comprehensive guidance on deploying machine learning on embedded devices. As edge computing and the Internet of Things proliferate, this textbook provides professionals and students the expertise to implement performant AI on resource-constrained hardware. A unique aspect of this book elucidates the entire machine learning workflow, from data engineering through training, optimization, acceleration, and production deployment. Key topics covered include deep learning and classical ML algorithms for embedded systems, efficient neural network architectures, hardware-aware training techniques, model compression, benchmarking for tinyML, and on-device learning. Additional chapters highlight cutting-edge advances like on-device data generation and crucial considerations around reliability, privacy, security, and responsible AI. With its rigorous approach spanning theory and practice across diverse tinyML application domains like smart homes, wearables, and industrial IoT, the book enables readers to develop specialized knowledge. Using concrete use cases and hands-on examples, readers will learn to apply machine learning to transform embedded and IoT systems. Overall, this indispensable guide provides a research-based foundation for leveraging machine learning in embedded systems. + book: page-navigation: true title: "MACHINE LEARNING SYSTEMS for tinyML"