Artificial Intelligence for IoT Cookbook: Over 70 recipes for building AI solutions for smart homes, industrial IoT, and smart cities

This book provides practical insights and techniques for implementing machine learning and deep learning in IoT applications, covering topics such as data collection, analysis, modeling, and deployment. It uses real-life datasets and examples to demonstrate how to build intelligent systems that can extract valuable insights from IoT data.

Format: Paperback / softback
Length: 260 pages
Publication date: 05 March 2021
Publisher: Packt Publishing Limited

Understand the basics of machine learning and deep learning for building smart IoT systems. Learn how to implement advanced techniques such as computer vision, natural language processing (NLP), and embedded machine learning. Build, maintain, and deploy machine learning systems to extract key insights from IoT data. Explore 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. Deploy models and improve their performance with ease. Package and deploy end-to-end AI apps and apply best practice solutions to common IoT problems.

Implement machine learning and deep learning techniques to perform predictive analytics on real-time IoT data

Key Features

Discover quick solutions to common problems that you'll face while building smart IoT applications

Implement advanced techniques such as computer vision, natural language processing (NLP), and embedded machine learning

Build, maintain, and deploy machine learning systems to extract key insights from IoT data

Book 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 learn

Understand the basics of machine learning and deep learning for building smart IoT systems.

Learn how to implement advanced techniques such as computer vision, natural language processing (NLP), and embedded machine learning.

Build, maintain, and deploy machine learning systems to extract key insights from IoT data.

Explore 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.

Deploy models and improve their performance with ease.

Package and deploy end-to-end AI apps and apply best practice solutions to common IoT problems.

Dimension: 93 x 75 (mm)
ISBN-13: 9781838981983