Sign In Start Free Trial
Account

Add to playlist

Create a Playlist

Modal Close icon
You need to login to use this feature.
  • Artificial Intelligence for IoT Cookbook
  • Toc
  • feedback
Artificial Intelligence for IoT Cookbook

Artificial Intelligence for IoT Cookbook

By : Roshak
4.9 (10)
close
Artificial Intelligence for IoT Cookbook

Artificial Intelligence for IoT Cookbook

4.9 (10)
By: Roshak

Overview of this book

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.
Table of Contents (11 chapters)
close
Machine Learning for IoT

Machine learning has dramatically altered what manufacturers are able to do with IoT. Today, there are numerous industries that have specific IoT needs. For example, the internet of medical things (IoMT) has devices such as outpatient heart monitors that can be worn at home. These devices often require large amounts of data to be sent over the network or large compute capacity on the edge to process heart-related events. Another example is agricultural IoT (AIoT) devices that are often placed in locations where there is no Wi-Fi or cellular network. Prescriptions or models are pushed down to these semi-connected devices. Many of these devices require that decisions be made on the edge. When connectivity is finally established using technology such as LoRAWAN or TV, white space models are downloaded to the devices.

In this chapter, we are going to...

Unlock full access

Continue reading for free

A Packt free trial gives you instant online access to our library of over 7000 practical eBooks and videos, constantly updated with the latest in tech
bookmark search playlist download font-size

Change the font size

margin-width

Change margin width

day-mode

Change background colour

Close icon Search
Country selected

Close icon Your notes and bookmarks

Delete Bookmark

Modal Close icon
Are you sure you want to delete it?
Cancel
Yes, Delete