Book Image

Artificial Intelligence with Power BI

By : Mary-Jo Diepeveen
Book Image

Artificial Intelligence with Power BI

By: Mary-Jo Diepeveen

Overview of this book

The artificial intelligence (AI) capabilities in Power BI enable organizations to quickly and easily gain more intelligent insights from unstructured and structured data. This book will teach you how to make use of the many AI features available today in Power BI to quickly and easily enrich your data and gain better insights into patterns that can be found in your data. You’ll begin by understanding the benefits of AI and how it can be used in Power BI. Next, you’ll focus on exploring and preparing your data for building AI projects and then progress to using prominent AI features already available in Power BI, such as forecasting, anomaly detection, and Q&A. Later chapters will show you how to apply text analytics and computer vision within Power BI reports. This will help you create your own Q&A functionality in Power BI, which allows you to ask FAQs from another knowledge base and then integrate it with PowerApps. Toward the concluding chapters, you’ll be able to create and deploy AutoML models trained in Azure ML and consume them in Power Query Editor. After your models have been trained, you’ll work through principles such as privacy, fairness, and transparency to use AI responsibly. By the end of this book, you’ll have learned when and how to enrich your data with AI using the out-of-the-box AI capabilities in Power BI.
Table of Contents (18 chapters)
Part 1: AI Fundamentals
Part 2: Out-of-the-Box AI Features
Part 3: Create Your Own Models

Working with Azure ML

Learning how to work with Azure ML is worth multiple books by itself. Azure ML is designed to help data scientists create and manage machine learning models that can be trained with the often-preferred Python framework.

In this section, we'll cover the basics of the Azure ML service that may interest you as a data analyst. We'll also touch upon some concepts within the service that are reserved for more advanced users so that you know what to explore further.

There are three approaches to working with Azure ML:

  • Using the online UI called Azure Machine Learning Studio. This is a user-friendly approach that you can access at
  • Using the Python SDK. This is mostly preferred by data scientists who are already familiar with Python and want to work with the Azure ML service programmatically.
  • Using the Azure CLI extension for Azure ML. This is mostly preferred by administrators and machine learning engineers who...