Hands-On Artificial Intelligence for IoT

Expert machine learning and deep learning techniques for developing smarter IoT systems

Publisher:Packt Publishing Limited

By: Dr. Amita Kapoor

Paid access

|May 2025

E-Book €26.99Institutions €125.95

Description

Master AI and IoT integration, from fundamentals to advanced techniques, and revolutionize your approach to building intelligent, data-driven solutions across industries

Key Features

Leverage the power of Python libraries such as TensorFlow and Keras to work with real-time IoT data
Enhance your IoT solutions with advanced AI techniques, including deep learning, optimization, and generative adversarial networks
Gain practical insights through industry-specific IoT case studies in manufacturing, smart cities, and automation
Purchase of the print or Kindle book includes a free PDF eBook

Book Description

Transform IoT devices into intelligent systems with this comprehensive guide by Amita Kapoor, Chief AI Officer at Tipz AI. Drawing on 25 years of expertise in developing intelligent systems across industries, she demonstrates how to harness the combined power of artificial intelligence and IoT technology. A pioneer in making AI and neuroscience education accessible worldwide, Amita guides you through creating smart, efficient systems that leverage the latest advances in both fields. This new edition is updated with various optimization techniques in IoT used for enhancing efficiency and performance. It introduces you to cloud platforms such as Platform as a Service (PaaS) and Infrastructure as a Service (IaaS) for analyzing data generated using IoT devices. You’ll learn about machine learning algorithms, deep learning techniques, and practical applications in real-world IoT scenarios and advance to creating AI models that work with diverse data types, including time series, images, and audio. You’ll also harness the power of widely used Python libraries, TensorFlow and Keras, to build a variety of smart AI models. By the end of the book, you’ll emerge as a master of AI-driven IoT, armed with invaluable experience in optimizing IoT devices, boosting their performance, and integrating AI algorithms to make intelligent decisions.

What you will learn

Integrate AI and IoT for enhanced device intelligence
Understand how to build scalable and efficient IoT systems
Master both supervised and unsupervised machine learning techniques for processing IoT data
Explore the full potential of deep learning in IoT applications
Discover AI-driven strategies to optimize IoT system efficiency
Implement real-world IoT projects that leverage AI capabilities
Improve device performance and decision-making using AI algorithms

Who this book is for

This book is for IoT developers, engineers, and tech enthusiasts, particularly those with a background in Python, looking to integrate artificial intelligence and machine learning into IoT systems. Python developers eager to apply their knowledge in new, innovative ways will find it useful. It’s also an invaluable guide for anyone with a foundational understanding of IoT concepts ready to take their skills to the next level and shape the future of intelligent devices.

Principles and Foundations of IoT and AI
Data Access and Distributed Processing for IoT
Machine Learning for IoT
Deep Learning for IoT
Optimization Techniques in IoT
Reinforcement Learning for IoT
Generative Adversarial Networks for IoT
Distributed AI for IoT
AI Cloud Platforms for IoT
Deep Learning for Time Series Data from IoT
AI for Video and Image Data from IoT
AI for Text, Audio and Speech Data from IoT
AI for Personal and Home IoT
AI for Industrial IoT
AI for Smart Cities IoT

https://github.com/PacktPublishing/Hands-On-Artificial-Intelligence-for-IoT-Second-Edition

PDF ISBN: 978-1-83546-296-6

Publisher: Packt Publishing Limited

Publication date: 2025

Language: English

Pages: 472

Related subjects:

Computer sciences,

Artificial intelligence

Hands-On Artificial Intelligence for IoT

Key Features

Book Description

What you will learn

Who this book is for

Table of Contents

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