Machine Learning with the Raspberry Pi - Experiments with Data and Computer Vision (Paperback, 1st ed.)

Using the Pi Camera and a Raspberry Pi board, expand and replicate interesting machine learning (ML) experiments. This book provides a solid overview of ML and a myriad of underlying topics to further explore. Non-technical discussions temper complex technical explanations to make the hottest and most complex topic in the hobbyist world of computing understandable and approachable. Machine learning, also commonly referred to as deep learning (DL), is currently being integrated into a multitude of commercial products as well as widely being used in industrial, medical, and military applications. It is hard to find any modern human activity, which has not been "touched" by artificial intelligence (AI) applications. Building on the concepts first presented in Beginning Artificial Intelligence with the Raspberry Pi, you'll go beyond simply understanding the concepts of AI into working with real machine learning experiments and applying practical deep learning concepts to experiments with the Pi board and computer vision. What you learn with Machine Learning with the Raspberry Pi can then be moved on to other platforms to go even further in the world of AI and ML to better your hobbyist or commercial projects. What You'll Learn Acquire a working knowledge of current ML Use the Raspberry Pi to implement ML techniques and algorithms Apply AI and ML tools and techniques to your own work projects and studies Who This Book Is For Engineers and scientists but also experienced makers and hobbyists. Motivated high school students who desire to learn about ML can benefit from this material with determination.

General

Imprint:	Apress
Country of origin:	United States
Release date:	February 2020
First published:	2020
Authors:	Donald J. Norris
Dimensions:	235 x 155 x 35mm (L x W x T)
Format:	Paperback
Pages:	568
Edition:	1st ed.
ISBN-13:	978-1-4842-5173-7
Categories:	Books > Computing & IT > Computer hardware & operating systems > General
LSN:	1-4842-5173-3
Barcode:	9781484251737

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