Hands On Deep Learning For Iot
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Hands-On Artificial Intelligence for IoT
Author: Dr. Amita Kapoor
language: en
Publisher: Packt Publishing Ltd
Release Date: 2025-05-16
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 DescriptionTransform 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.
Hands-On Deep Learning for IoT
Author: Md. Rezaul Karim
language: en
Publisher: Packt Publishing Ltd
Release Date: 2019-06-27
Implement popular deep learning techniques to make your IoT applications smarter Key FeaturesUnderstand how deep learning facilitates fast and accurate analytics in IoTBuild intelligent voice and speech recognition apps in TensorFlow and ChainerAnalyze IoT data for making automated decisions and efficient predictionsBook Description Artificial Intelligence is growing quickly, which is driven by advancements in neural networks(NN) and deep learning (DL). With an increase in investments in smart cities, smart healthcare, and industrial Internet of Things (IoT), commercialization of IoT will soon be at peak in which massive amounts of data generated by IoT devices need to be processed at scale. Hands-On Deep Learning for IoT will provide deeper insights into IoT data, which will start by introducing how DL fits into the context of making IoT applications smarter. It then covers how to build deep architectures using TensorFlow, Keras, and Chainer for IoT. You’ll learn how to train convolutional neural networks(CNN) to develop applications for image-based road faults detection and smart garbage separation, followed by implementing voice-initiated smart light control and home access mechanisms powered by recurrent neural networks(RNN). You’ll master IoT applications for indoor localization, predictive maintenance, and locating equipment in a large hospital using autoencoders, DeepFi, and LSTM networks. Furthermore, you’ll learn IoT application development for healthcare with IoT security enhanced. By the end of this book, you will have sufficient knowledge need to use deep learning efficiently to power your IoT-based applications for smarter decision making. What you will learnGet acquainted with different neural network architectures and their suitability in IoTUnderstand how deep learning can improve the predictive power in your IoT solutionsCapture and process streaming data for predictive maintenanceSelect optimal frameworks for image recognition and indoor localizationAnalyze voice data for speech recognition in IoT applicationsDevelop deep learning-based IoT solutions for healthcareEnhance security in your IoT solutionsVisualize analyzed data to uncover insights and perform accurate predictionsWho this book is for If you’re an IoT developer, data scientist, or deep learning enthusiast who wants to apply deep learning techniques to build smart IoT applications, this book is for you. Familiarity with machine learning, a basic understanding of the IoT concepts, and some experience in Python programming will help you get the most out of this book.
Hands-On Artificial Intelligence for IoT - Second Edition
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. Table of Contents - 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