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Machine Learning with the Raspberry Pi
Experiments with Data and Computer Vision | Norris, Donald J.
Taschenbuch
2019 Apress
Auflage: 1. Auflage
IX, 568 Seiten; IX, 568 p. 229 illus.; 23.5 cm x 15.5 cm
Sprache: English
ISBN: 978-1-4842-5173-7
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Inhalt
sonstiger Text 978-1-4842-5173-7 Inhaltsverzeichnis GB Machine Learning with the Raspberry Pi
Chapter 1: Foundational items
Chapter 2: Modeling fundamentals:
Chapter 3: Algorithmic approaches
Chapter 4: Supervised/unsupervised learning
Chapter 5: Reinforcement learning
Klappentext Donald Norris is an avid electronics hobbyist and maker. He is also an electronics engineer with an advanced degree in Production Management. Don is retired from civilian government service with the US Navy, where he specialized in acoustics and digital signal processing. He also has more than a dozen years' experience as a professional software developer using C, C#, C++, Python, and Java, as well as five years' experience as a certified IT security consultant.
Donald Norris is an avid electronics hobbyist and maker. He is also an electronics engineer with an advanced degree in Production Management. Don is retired from civilian government service with the US Navy, where he specialized in acoustics and digital signal processing. He also has more than a dozen years' experience as a professional software developer using C, C#, C++, Python, and Java, as well as five years' experience as a certified IT security consultant. Klappentext GB 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.
Autorentext: §16§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.
§04§Machine Learning with the Raspberry Pi
Chapter 1: Foundational items
Chapter 2: Modeling fundamentals:
Chapter 3: Algorithmic approaches
Chapter 4: Supervised/unsupervised learning
Chapter 5: Reinforcement learning
§15§Donald Norris is an avid electronics hobbyist and maker. He is also an electronics engineer with an advanced degree in Production Management. Don is retired from civilian government service with the US Navy, where he specialized in acoustics and digital signal processing. He also has more than a dozen years' experience as a professional software developer using C, C#, C++, Python, and Java, as well as five years' experience as a certified IT security consultant.§15§Donald Norris is an avid electronics hobbyist and maker. He is also an electronics engineer with an advanced degree in Production Management. Don is retired from civilian government service with the US Navy, where he specialized in acoustics and digital signal processing. He also has more than a dozen years' experience as a professional software developer using C, C#, C++, Python, and Java, as well as five years' experience as a certified IT security consultant.
sonstiger Text 978-1-4842-5173-7 Inhaltsverzeichnis GB Machine Learning with the Raspberry Pi
Chapter 1: Foundational items
Chapter 2: Modeling fundamentals:
Chapter 3: Algorithmic approaches
Chapter 4: Supervised/unsupervised learning
Chapter 5: Reinforcement learning
Klappentext Donald Norris is an avid electronics hobbyist and maker. He is also an electronics engineer with an advanced degree in Production Management. Don is retired from civilian government service with the US Navy, where he specialized in acoustics and digital signal processing. He also has more than a dozen years' experience as a professional software developer using C, C#, C++, Python, and Java, as well as five years' experience as a certified IT security consultant.
Donald Norris is an avid electronics hobbyist and maker. He is also an electronics engineer with an advanced degree in Production Management. Don is retired from civilian government service with the US Navy, where he specialized in acoustics and digital signal processing. He also has more than a dozen years' experience as a professional software developer using C, C#, C++, Python, and Java, as well as five years' experience as a certified IT security consultant. Klappentext GB 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.
Autorentext: §16§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.
§04§Machine Learning with the Raspberry Pi
Chapter 1: Foundational items
Chapter 2: Modeling fundamentals:
Chapter 3: Algorithmic approaches
Chapter 4: Supervised/unsupervised learning
Chapter 5: Reinforcement learning
§15§Donald Norris is an avid electronics hobbyist and maker. He is also an electronics engineer with an advanced degree in Production Management. Don is retired from civilian government service with the US Navy, where he specialized in acoustics and digital signal processing. He also has more than a dozen years' experience as a professional software developer using C, C#, C++, Python, and Java, as well as five years' experience as a certified IT security consultant.§15§Donald Norris is an avid electronics hobbyist and maker. He is also an electronics engineer with an advanced degree in Production Management. Don is retired from civilian government service with the US Navy, where he specialized in acoustics and digital signal processing. He also has more than a dozen years' experience as a professional software developer using C, C#, C++, Python, and Java, as well as five years' experience as a certified IT security consultant.