Discover the world of TinyML - an approach to machine learning that focuses on using artificial intelligence directly on small devices (e.g., microcontrollers) and on processing data locally, often without the need for a constant internet connection or powerful servers.

This book is intended for anyone who wants to get acquainted with technologies that combine sensors, data, and edge computing in real time. TinyML can help to better understand the possibilities of automation, smart devices, and IoT, with an emphasis on low power consumption and fast response in typical use scenarios.

Thanks to its clear presentation and emphasis on practical use, the book TinyML can make it easier for you to enter the field of AI on miniature hardware. It is suitable for beginners as well as more advanced readers who want to expand their knowledge in machine learning and edge devices.

Why TinyML?

• Small devices, big possibilities: An introduction to the principles of deploying AI on sensors and microcontrollers.
• Energy savings: An explanation of techniques and trade-offs used in practice for low power consumption.
• Fast response: Local data processing without the need to send everything to the cloud.
• Wide range of applications: IoT, wearable electronics, industrial applications, and more.
• Support for learning and innovation: Suitable for study and inspiration for your own projects.

Key product features

• An introduction to implementing TinyML and related concepts across common platforms.
• Practical examples and procedures that can facilitate getting started and further work.
• Tips for integrating models into existing devices and workflows.
• An overview of selected approaches and tools used in edge machine learning.
• Useful for developers as well as tech enthusiasts and students.