What this book covers
Chapter 1, Principles and Foundations of IoT and AI, introduces the basic concepts IoT, AI, and data science. We end the chapter with an introduction to the tools and datasets we will be using in the book.
Chapter 2, Data Access and Distributed Processing for IoT, covers various methods of accessing data from various data sources, such as files, databases, distributed data stores, and streaming data.
Chapter 3, Machine Learning for IoT, covers the various aspects of machine learning, such as supervised, unsupervised, and reinforcement learning for IoT. The chapter ends with tips and tricks to improve your models' performance.
Chapter 4, Deep Learning for IoT, explores the various aspects of deep learning, such as MLP, ...
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