Book Image

Artificial Intelligence for IoT Cookbook

By : Michael Roshak
Book Image

Artificial Intelligence for IoT Cookbook

By: Michael 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)

Enhancing bots with QnA Maker

Microsoft's QnA Maker is a tool that can take frequently asked questions (FAQs) and turn them into a set of questions and answers using language understanding, allowing users to ask questions differently to get an answer that matches up to the question. QnA Maker can take in a list of tab-separated values (TSVs), an FAQ web page, and a PDF, to name a few. In this recipe, we will use a TSV with questions and answers.

QnA Maker solves the fuzzy logic of interpreting speech and determining the user's question. As part of the Cognitive Service speech ecosystem, it can be incorporated easily with Bot Framework and voice to give customers a rich interactive experience.