A contemporary discussion of real-world TinyML development

In TinyML: Revolutionizing Embedded AI for Intelligent Devices, a team of distinguished researchers delivers an expert, up-to-date discussion of the practical applications of TinyML. The authors explain how to develop smart systems that learn and make decisions at the place of action on tiny, low-power devices.

Readers will learn how to create systems that act without access to high-speed internet connectivity. Beginning with explanations of the fundamentals of TinyML, the hardware it runs on, and how to collect and prepare the data required to run applications, the book goes on to discuss neural networks, model training, and the wide array of real-world applications and examples of the technologies.

Readers will also discover:

• A thorough introduction to the data privacy and security problems inherent in TinyML development
• Comprehensive explorations of the hands-on techniques required to develop TinyML applications
• Practical discussions of the hardware and software ecosystems in which TinyML development occurs
• Complete treatments of clustering, neural network architectures, and likely future developments in those areas

Perfect for data scientists and machine learning engineers, TinyML will also benefit embedded systems engineers, IoT developers, and students of computer science, electrical engineering, and robotics.