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

Chapter 12: Training a Model with Azure Machine Learning

Throughout this book, we have explored many of the features in Power BI that allow us to apply machine learning without having to train a model. However, you may still encounter a situation where it is necessary to train your model on your data.

To train a model and integrate it easily with Power BI, you can use Azure Machine Learning (Azure ML). In this chapter, we'll learn how we can use the Azure ML service to create a machine learning model and deploy it to an endpoint. This endpoint can then be integrated with Power BI to get predictions on the data residing in Power BI.

In this chapter, we're going to cover the following topics:

  • Understanding how to train a model
  • Working with Azure Machine Learning
  • Training a model with Azure Machine Learning Designer
  • Deploying a model for batch or real-time predictions
  • Integrating an endpoint with Power BI to generate predictions

As Azure...