Название: AI and Machine Learning for On-Device Development: A Programmer’s Guide (Second Early Release)
Автор: Laurence Moroney
Издательство: O’Reilly Media, Inc.
Год: 2021-06-18
Страниц: 111
Язык: английский
Формат: epub
Размер: 22.7 MB
AI is nothing without somewhere to run it. Now that mobile devices have become the primary computing device for most people, it's essential that mobile developers add AI to their toolbox. This insightful book is your guide to creating models and running them on popular mobile platforms such as iOS and Android.
You’ve likely picked this book up because you’re curious about Artificial Intelligence (AI), Machine Learning (ML), Deep Learning and all of the new technologies that promise the latest and greatest breakthroughs. Welcome! In this book, my goal is to explain a little about how AI and ML work, and a lot about how you can put them to work for you in your mobile apps using technologies such as TensorFlow Lite, ML Kit and CoreML. We’ll start light, in the Chapter 1, by establishing what we actually mean when we describe Artificial intelligence, Machine Learning, Deep Learning and more.
Given how often AI is seen in these ways, it’s easy to come to the conclusion that they define AI. However, none of these are actual definitions or examples of what Artificial Intelligence is, at least in today’s terms. It’s not the artificial creation of intelligence -- it’s the artificial appearance of intelligence. When you become an AI developer, you’re not building a new lifeform -- you’re writing code that acts in a different way to traditional code, and that can very loosely emulate the way an intelligence reacts to something. Common areas of these are to use deep learning for Computer Vision where, instead of you writing code that tries to understand the contents of an image with a lot of if..then rules that parse the pixels,, you can instead have a computer learn what the contents are by ‘looking’ at lots of samples.
Explore the options for implementing ML and AI on mobile devices--and when to use each
Create ML models for iOS and Android
Write ML Kit and TensorFlow Lite apps for iOS and Android and Core ML/Create ML apps for iOS
Understand how to choose the best techniques and tools for your use case: on-device inference versus cloud-based inference, high-level APIs versus low-level APIs, and more
Learn privacy and ethics best practices for ML on devices
Автор: Laurence Moroney
Издательство: O’Reilly Media, Inc.
Год: 2021-06-18
Страниц: 111
Язык: английский
Формат: epub
Размер: 22.7 MB
AI is nothing without somewhere to run it. Now that mobile devices have become the primary computing device for most people, it's essential that mobile developers add AI to their toolbox. This insightful book is your guide to creating models and running them on popular mobile platforms such as iOS and Android.
You’ve likely picked this book up because you’re curious about Artificial Intelligence (AI), Machine Learning (ML), Deep Learning and all of the new technologies that promise the latest and greatest breakthroughs. Welcome! In this book, my goal is to explain a little about how AI and ML work, and a lot about how you can put them to work for you in your mobile apps using technologies such as TensorFlow Lite, ML Kit and CoreML. We’ll start light, in the Chapter 1, by establishing what we actually mean when we describe Artificial intelligence, Machine Learning, Deep Learning and more.
Given how often AI is seen in these ways, it’s easy to come to the conclusion that they define AI. However, none of these are actual definitions or examples of what Artificial Intelligence is, at least in today’s terms. It’s not the artificial creation of intelligence -- it’s the artificial appearance of intelligence. When you become an AI developer, you’re not building a new lifeform -- you’re writing code that acts in a different way to traditional code, and that can very loosely emulate the way an intelligence reacts to something. Common areas of these are to use deep learning for Computer Vision where, instead of you writing code that tries to understand the contents of an image with a lot of if..then rules that parse the pixels,, you can instead have a computer learn what the contents are by ‘looking’ at lots of samples.
Explore the options for implementing ML and AI on mobile devices--and when to use each
Create ML models for iOS and Android
Write ML Kit and TensorFlow Lite apps for iOS and Android and Core ML/Create ML apps for iOS
Understand how to choose the best techniques and tools for your use case: on-device inference versus cloud-based inference, high-level APIs versus low-level APIs, and more
Learn privacy and ethics best practices for ML on devices
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