Artificial Intelligence for IoT Cookbook

More Information
  • Explore a variety of AI techniques to build smart IoT solutions from scratch
  • Infuse machine learning and deep learning techniques to build smart voice recognition and facial detection systems
  • Get insights into IoT data using algorithms and implement them in your projects
  • Perform anomaly detection for time-series data and other types of IoT data
  • Implement reinforcement learning techniques for a smart traffic intersection
  • Apply pre-trained machine learning models to an edge device
  • Deploy machine learning models to web applications and mobile using TensorFlow.js and ONNX

Artificial intelligence (AI) is rapidly finding practical applications across all industry verticals, and IoT is one of them. Developers are looking for ways to make IoT devices smarter and to make users’ lives easier. With this book, you’ll be able to implement smart analytics using IoT data to gain insights, predict outcomes, and make informed decisions.

This AI cookbook will provide an overview of advanced AI techniques that facilitate analytics and learning in various IoT applications. Using the recipe-based approach, you’ll be taken through each process including data collection, analysis, modeling, statistics and monitoring, and deployment. You’ll use real-life datasets of smart homes, Industrial IoT, and smart devices to train and evaluate simple-to-complex models and make predictions using trained models. The book also covers the key challenges faced while implementing machine learning and deep learning and other AI techniques such as natural language processing (NLP), computer vision, and reinforcement learning for building smart IoT systems. Additionally, 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 applications and implement best practice solutions to common IoT problems.

  • Discover quick solutions to common problems that you’ll face while building smart IoT applications
  • Implement advanced techniques such as computer vision, NLP, and reinforcement learning
  • Build, maintain, and deploy machine learning systems to extract key insights from IoT data
Page Count 69
Course Length 2 hours 4 minutes
ISBN 9781838981983
Date Of Publication 4 Sep 2020


Michael Roshak

Michael Roshak is a cloud architect and strategist with extensive subject matter expertise in enterprise cloud transformation programs and infrastructure modernization through designing, and deploying cloud-oriented solutions and architectures. He is responsible for providing strategic advisory for cloud adoption, consultative technical sales, and driving broad cloud services consumption with highly strategic accounts across multiple industries.