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Artificial Intelligence for IoT Cookbook

Artificial Intelligence for IoT Cookbook

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

Artificial Intelligence for IoT Cookbook

4.9 (10)
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)
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Getting ready

In this recipe, we are going to spin up a Docker instance of a SQL Server database. To get started, you must install Docker.

The next step is to build and run a SQL Server database using docker:

docker pull mcr.microsoft.com/mssql/server:2017-latest 

 Then, run the Docker container:

docker run -e 'ACCEPT_EULA=Y' -e 'MSSQL_AGENT_ENABLED=true' \
-e 'MSSQL_PID=Standard' -e 'SA_PASSWORD=Password!' \
-p 1433:1433 --name sqlserver_1 \
-d mcr.microsoft.com/mssql/server:2017-latest

Now that we have a working SQL Server database, we need to add a database and two tables for it. You can connect to the SQL database by installing the mssql plugin for VS Code and then connecting to the database with the username and password we had in the Docker file:

Once you've done this, click on the new SQL Server tool in the left panel. Then, click on the plus (+) button...

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