Ebook: AI and Machine Learning for On-Device Development: A Programmer's Guide
Author: Laurence Moroney
- Genre: Computers // Cybernetics: Artificial Intelligence
- Tags: Cloud Computing, Machine Learning, Deep Learning, Computer Vision, Ethics, iOS, Privacy, Docker, Android, AutoML, Text Processing, Kotlin, Mobile Applications, TensorFlow Lite, ML Kit
- Year: 2021
- Publisher: O'Reilly Media
- City: Sebastopol, CA
- Edition: 1
- Language: English
- pdf
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 and running models on popular mobile platforms such as iOS and Android.
Laurence Moroney, lead AI advocate at Google, offers an introduction to machine learning techniques and tools, then walks you through writing Android and iOS apps powered by common ML models like computer vision and text recognition, using tools such as ML Kit, TensorFlow Lite, and Core ML. If you're a mobile developer, this book will help you take advantage of the ML revolution today.
• Explore the options for implementing ML and AI on mobile devices
• 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
• Choose the best techniques and tools for your use case, such as cloud-based versus on-device inference and high-level versus low-level APIs
• Learn privacy and ethics best practices for ML on devices
Laurence Moroney, lead AI advocate at Google, offers an introduction to machine learning techniques and tools, then walks you through writing Android and iOS apps powered by common ML models like computer vision and text recognition, using tools such as ML Kit, TensorFlow Lite, and Core ML. If you're a mobile developer, this book will help you take advantage of the ML revolution today.
• Explore the options for implementing ML and AI on mobile devices
• 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
• Choose the best techniques and tools for your use case, such as cloud-based versus on-device inference and high-level versus low-level APIs
• Learn privacy and ethics best practices for ML on devices
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