Python Programming Recipes For Iot Applications

Python Programming Recipes for IoT Applications

The book comprehensively covers the most important applications of the internet of things (IoT) using Python programming on Raspberry pi, Micropython Py Board, and NVIDIA Jetson Board. The authors have used an immersive ‘hands-on’ approach to help readers gain expertise in developing working code for real-world IoT applications. The book focuses on industry-standard embedded platforms for IoT applications. It also gives a glimpse of python programming and setup configuration of these embedded platforms. The later chapter highlights basic interface applications with Raspberry Pi. Exclusive advanced IoT applications on the Micropython Pyboard are also covered. The last two chapters deal with the NVIDIA Jetson Nano board programming for machine learning applications with FoG/cloud computing. The various IoT applications with different embedded platforms in this volume are best-suited for undergraduate/postgraduate students and researchers who want to get exposed to python programming for IoT applications. This book will enable readers to design their own embedded IoT products.

PRACTICAL PYTHON PROGRAMMING FOR IOT

Artificial Intelligence for IoT Cookbook

Implement machine learning and deep learning techniques to perform predictive analytics on real-time IoT data Key FeaturesDiscover quick solutions to common problems that you'll face while building smart IoT applicationsImplement advanced techniques such as computer vision, NLP, and embedded machine learningBuild, maintain, and deploy machine learning systems to extract key insights from IoT dataBook Description Artificial intelligence (AI) is rapidly finding practical applications across a wide variety of industry verticals, and the Internet of Things (IoT) is one of them. Developers are looking for ways to make IoT devices smarter and to make users' lives easier. With this AI cookbook, you'll be able to implement smart analytics using IoT data to gain insights, predict outcomes, and make informed decisions, along with covering advanced AI techniques that facilitate analytics and learning in various IoT applications. Using a recipe-based approach, the book will take you through essential processes such as data collection, data analysis, modeling, statistics and monitoring, and deployment. You'll use real-life datasets from smart homes, industrial IoT, and smart devices to train and evaluate simple to complex models and make predictions using trained models. Later chapters will take you through the key challenges faced while implementing machine learning, deep learning, and other AI techniques, such as natural language processing (NLP), computer vision, and embedded machine learning for building smart IoT systems. In addition to this, you'll learn how to deploy models and improve their performance with ease. By the end of this book, you'll be able to package and deploy end-to-end AI apps and apply best practice solutions to common IoT problems. What you will learnExplore various AI techniques to build smart IoT solutions from scratchUse machine learning and deep learning techniques to build smart voice recognition and facial detection systemsGain insights into IoT data using algorithms and implement them in projectsPerform anomaly detection for time series data and other types of IoT dataImplement embedded systems learning techniques for machine learning on small devicesApply pre-trained machine learning models to an edge deviceDeploy machine learning models to web apps and mobile using TensorFlow.js and JavaWho this book is for If you're an IoT practitioner looking to incorporate AI techniques to build smart IoT solutions without having to trawl through a lot of AI theory, this AI IoT book is for you. Data scientists and AI developers who want to build IoT-focused AI solutions will also find this book useful. Knowledge of the Python programming language and basic IoT concepts is required to grasp the concepts covered in this artificial intelligence book more effectively.