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Artificial Intelligence for IoT Cookbook

Artificial Intelligence for IoT Cookbook

By : Roshak
4.9 (10)
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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)
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Visual exploration

Spark allows you to look at basic charts without much code. Using the magic symbol at the top of the notebook segment, you can change language easily from Python to Scala or SQL. One word of caution about using Databricks' built-in charting system is that it only looks at the first 10,000 records. For a large dataset, there are other charting libraries. The steps are as follows:

  1. Query the data in Databricks using the %sql magic, as shown:
%sql
select * from Telemetry
  1. Select the chart icon at the bottom of the returned data grid. It will bring up the chart builder UI, as shown in the following screenshot:

  1. Select the chart type that best represents the data. Some charts are better suited for variable comparison while others can help reveal trends.

The following section reviews when and why you would use different chart types.

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