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Artificial Intelligence with Power BI

Artificial Intelligence with Power BI
Author: Mary-Jo Diepeveen
Publisher: Packt Publishing Ltd
Total Pages: 348
Release: 2022-04-29
Genre: Computers
ISBN: 1801816255
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Learn how to create your own AI model and consume it in your Power BI reports to gain better insights from your data Key FeaturesLearn how to gain better insights from your data by applying different AI techniques within Power BISave time by creating machine learning models independently and integrating them within your BI reportsUnderstand how to combine Cognitive Services and Azure Machine Learning together with Power BIBook Description 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. What you will learnApply techniques to mitigate bias and handle outliers in your dataPrepare time series data for forecasting in Power BIPrepare and shape your data for anomaly detectionUse text analytics in Power Query EditorIntegrate QnA Maker with PowerApps and create an appTrain your own models and identify the best one with AutoMLIntegrate an Azure ML workspace with Power BI and use endpoints to generate predictionsWho this book is for This artificial intelligence BI book is for data analysts and BI developers who want to explore advanced analytics or artificial intelligence possibilities with their data. Prior knowledge of Power BI will help you get the most out of this book.

Artificial Intelligence with Microsoft Power BI

Artificial Intelligence with Microsoft Power BI
Author: Jen Stirrup
Publisher: "O'Reilly Media, Inc."
Total Pages: 473
Release: 2024-03-28
Genre: Computers
ISBN: 1098112725
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Advance your Power BI skills by adding AI to your repertoire at a practice level. With this practical book, business-oriented software engineers and developers will learn the terminologies, practices, and strategy necessary to successfully incorporate AI into your business intelligence estate. Jen Stirrup, CEO of AI and BI leadership consultancy Data Relish, and Thomas Weinandy, research economist at Upside, show you how to use data already available to your organization. Springboarding from the skills that you already possess, this book adds AI to your organization's technical capability and expertise with Microsoft Power BI. By using your conceptual knowledge of BI, you'll learn how to choose the right model for your AI work and identify its value and validity. Use Power BI to build a good data model for AI Demystify the AI terminology that you need to know Identify AI project roles, responsibilities, and teams for AI Use AI models, including supervised machine learning techniques Develop and train models in Azure ML for consumption in Power BI Improve your business AI maturity level with Power BI Use the AI feedback loop to help you get started with the next project

Self-Service AI with Power BI Desktop

Self-Service AI with Power BI Desktop
Author: Markus Ehrenmueller-Jensen
Publisher: Apress
Total Pages: 344
Release: 2020-10-01
Genre: Computers
ISBN: 9781484262306
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This book explains how you can enrich the data you have loaded into Power BI Desktop by accessing a suite of Artificial Intelligence (AI) features. These AI features are built into Power BI Desktop and help you to gain new insights from existing data. Some of the features are automated and are available to you at the click of a button or through writing Data Analysis Expressions (DAX). Other features are available through writing code in either the R, Python, or M languages. This book opens up the entire suite of AI features to you with clear examples showing when they are best applied and how to invoke them on your own datasets. No matter if you are a business user, analyst, or data scientist – Power BI has AI capabilities tailored to you. This book helps you learn what types of insights Power BI is capable of delivering automatically. You will learn how to integrate and leverage the use of the R and Python languages for statistics, how to integrate with Cognitive Services and Azure Machine Learning Services when loading data, how to explore your data by asking questions in plain English ... and more! There are AI features for discovering your data, characterizing unexplored datasets, and building what-if scenarios. There’s much to like and learn from this book whether you are a newcomer to Power BI or a seasoned user. Power BI Desktop is a freely available tool for visualization and analysis. This book helps you to get the most from that tool by exploiting some of its latest and most advanced features. What You Will Learn Ask questions in natural language and get answers from your data Let Power BI explain why a certain data point differs from the rest Have Power BI show key influencers over categories of data Access artificial intelligence features available in the Azure cloud Walk the same drill down path in different parts of your hierarchy Load visualizations to add smartness to your reports Simulate changes in data and immediately see the consequences Know your data, even before you build your first report Create new columns by giving examples of the data that you need Transform and visualize your data with the help of R and Python scripts Who This Book Is For For the enthusiastic Power BI user who wants to apply state-of-the-art artificial intelligence (AI) features to gain new insights from existing data. For end-users and IT professionals who are not shy of jumping into a new world of machine learning and are ready to make that step and take a deeper look into their data. For those wanting to step up their game from doing simple reporting and visualizations by making the move into diagnostic and predictive analysis.

AI-Powered Business Intelligence

AI-Powered Business Intelligence
Author: Tobias Zwingmann
Publisher: "O'Reilly Media, Inc."
Total Pages: 378
Release: 2022-06-10
Genre: Business & Economics
ISBN: 1098111427
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Use business intelligence to power corporate growth, increase efficiency, and improve corporate decision making. With this practical book featuring hands-on examples in Power BI with basic Python and R code, you'll explore the most relevant AI use cases for BI, including improved forecasting, automated classification, and AI-powered recommendations. And you'll learn how to draw insights from unstructured data sources like text, document, and image files. Author Tobias Zwingmann helps BI professionals, business analysts, and data analytics understand high-impact areas of artificial intelligence. You'll learn how to leverage popular AI-as-a-service and AutoML platforms to ship enterprise-grade proofs of concept without the help of software engineers or data scientists. Learn how AI can generate business impact in BI environments Use AutoML for automated classification and improved forecasting Implement recommendation services to support decision-making Draw insights from text data at scale with NLP services Extract information from documents and images with computer vision services Build interactive user frontends for AI-powered dashboard prototypes Implement an end-to-end case study for building an AI-powered customer analytics dashboard

Machine Learning with Microsoft Power BI

Machine Learning with Microsoft Power BI
Author: Greg Beaumont
Publisher:
Total Pages: 0
Release: 2023-05-31
Genre: Artificial intelligence
ISBN: 9781837636150
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Unleash the full potential of Power BI with the integration of AI and Machine Learning (ML) techniques.Key Features* Embrace the future of data analysis with this comprehensive guide to AI, AutoML, and Machine Learning Connectivity in Power BI.* Discover how to unlock the full potential of Power BI with advanced AI features.* Design visually stunning data presentations, and seamless integration of cutting-edge machine learning tools and technologies.Book DescriptionMicrosoft Power BI is the ultimate solution for businesses looking to make data-driven decisions and unlock the full potential of their data. Power BI makes it easy to connect to a variety of data sources, and create stunning, interactive dashboards, reports, and visualizations that will bring your data insights to life.This book features the best practices when using Power BI AutoML, AI features, AI visuals, R/Python integration, and Azure ML integration.The book will give you a step-by-step tutorial for using different AI and ML capabilities, along with expert tips and tricks. "Workshop Style" content will also allow you to replicate the content in the book for a hands-on experience. You'll get Step-by-step AI/ML coverage with replicable examples and references. Data Scientists will learn how to leverage AI and ML capabilities in Power BI to improve their existing solutions and workloads. From enhancing data visualizations, to building a SaaS AutoML Model, to integrating Enterprise Machine Learning Solutions in Azure ML, the book will unlock new capabilities in Power BI for readers. By the end of the book, readers will have a solid understanding of how to build an AutoML model in Power BI, integrate Azure ML and Azure Cognitive Services, leverage AI visuals, and understand R/Python integration with Power BI.What you will learn* Discover best practices for implementing AI and ML capabilities in Power BI* Learn how to integrate Azure ML and Azure Cognitive Services into Power BI* Explore how to build a SaaS AutoML model in Power BI* Gain an understanding of R/Python integration with Power BI* See how to enhance data visualizations using AI and ML capabilities in Power BI* Understand how to improve existing solutions and workloads using AI and ML capabilities in Power BI* Acquire tips and tricks for successfully using AI and ML capabilities in Power BI* Gain access to hands-on Workshop content to recreate the book lessonsWho This Book Is ForData Science Professionals who want use Power BI and deploy Machine Learning models in Azure.

Power BI Machine Learning and OpenAI

Power BI Machine Learning and OpenAI
Author: Greg Beaumont
Publisher: Packt Publishing Ltd
Total Pages: 308
Release: 2023-05-31
Genre: Computers
ISBN: 1837634335
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Unleash the full potential of Power BI with the integration of AI and machine learning techniques using OpenAI Purchase of the print or Kindle book includes a free PDF eBook Key Features Take flight with Power BI machine learning and OpenAI using hands-on examples from the FAA airline data Unlock the full potential of Power BI for advanced analytics using OpenAI Design stunning data presentations, seamless integration of machine learning tools and technologies with OpenAI Book Description Microsoft Power BI is the ultimate solution for businesses looking to make data-driven decisions and unlock the full potential of their data. Unleashing Your Data with Power BI Machine Learning and OpenAI is designed for data scientists and BI professionals seeking to improve their existing solutions and workloads using AI. The book explains the intricacies of the subject by using a workshop-style data story for data ingestion, data modeling, analytics, and predictive analytics with Power BI machine learning. Along the way, you'll learn about AI features, AI visuals, R/Python integration, and OpenAI integration. The workshop-style content allows you to practice all your learnings in real-life challenges and gain hands-on experience. Additionally, you'll gain an understanding of AI/ML, step by step, with replicable examples and references. From enhancing data visualizations to building SaaS Power BI ML models, and integrating Azure OpenAI, this book will help you unlock new capabilities in Power BI. By the end of this book, you'll be well-equipped to build ML models in Power BI, plan projects for both BI and ML, understand R/Python visuals with Power BI, and introduce OpenAI to enhance your analytics solutions. What you will learn Discover best practices for implementing AI and ML capabilities in Power BI along with integration of OpenAI into the solution Understand how to integrate OpenAI and cognitive services into Power BI Explore how to build a SaaS auto ML model within Power BI Gain an understanding of R/Python integration with Power BI Enhance data visualizations for ML feature discovery Discover how to improve existing solutions and workloads using AI and ML capabilities in Power BI with OpenAI Acquire tips and tricks for successfully using AI and ML capabilities in Power BI along with integration of OpenAI into the solution Who this book is for This book is for data science and BI professionals looking to expand their skill sets into Power BI machine learning and OpenAI. This book is also useful for data scientists, data analysts, and IT professionals who want to learn how to incorporate OpenAI into Power BI for advanced experience.

Advanced Analytics in Power BI with R and Python

Advanced Analytics in Power BI with R and Python
Author: Ryan Wade
Publisher: Apress
Total Pages: 330
Release: 2020-09-05
Genre: Computers
ISBN: 9781484258286
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This easy-to-follow guide provides R and Python recipes to help you learn and apply the top languages in the field of data analytics to your work in Microsoft Power BI. Data analytics expert and author Ryan Wade shows you how to use R and Python to perform tasks that are extremely hard to do, if not impossible, using native Power BI tools without Power BI Premium capacity. For example, you will learn to score Power BI data using custom data science models, including powerful models from Microsoft Cognitive Services. The R and Python languages are powerful complements to Power BI. They enable advanced data transformation techniques that are difficult to perform in Power BI in its default configuration, but become easier through the application of data wrangling features that languages such as R and Python support. If you are a BI developer, business analyst, data analyst, or a data scientist who wants to push Power BI and transform it from being just a business intelligence tool into an advanced data analytics tool, then this is the book to help you to do that. What You Will Learn Create advanced data visualizations through R using the ggplot2 package Ingest data using R and Python to overcome the limitations of Power Query Apply machine learning models to your data using R and Python Incorporate advanced AI in Power BI via Microsoft Cognitive Services, IBM Watson, and pre-trained models in SQL Server Machine Learning Services Perform string manipulations not otherwise possible in Power BI using R and Python Who This Book Is For Power users, data analysts, and data scientists who want to go beyond Power BI’s built-in functionality to create advanced visualizations, transform data in ways not otherwise supported, and automate data ingestion from sources such as SQL Server and Excel in a more succinct way

Pro Power BI Theme Creation

Pro Power BI Theme Creation
Author: Adam Aspin
Publisher: Apress
Total Pages: 303
Release: 2021-05-25
Genre: Computers
ISBN: 9781484270677
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Use JSON theme files to standardize the look of Power BI dashboards and reports. This book shows how you can create theme files using the Power BI Desktop application to define high-level formatting attributes for dashboards as well as how to tailor detailed formatting specifications for individual dashboard elements in JSON files. Standardize the look of your dashboards and apply formatting consistently over all your reports. The techniques in this book provide you with tight control over the presentation of all aspects of the Power BI dashboards and reports that you create. Power BI theme files use JSON (JavaScript Object Notation) as their structure, so the book includes a brief introduction to JSON as well as how it applies to Power BI themes. The book further includes a complete reference to all the current formatting definitions and JSON structures that are at your disposal for creating JSON theme files. Finally, the book includes dozens of theme files, from the simple to the most complex, that you can adopt and adapt to suit your own requirements. What You Will Learn Produce designer output without manually formatting every individual visual in a Power BI dashboard Standardize presentation for families of dashboard types Switch presentation styles in a couple of clicks Save dozens, or hundreds, of hours laboriously formatting dashboards Define enterprise-wide presentation standards Retroactively apply standard styles to existing dashboards Who This Book Is For Power BI users who want to save time by defining standardized formatting for their dashboards and reports, IT professionals who want to create corporate standards of dashboard presentation, and marketing and communication specialists who want to set organizational standards for dashboard delivery

Introducing Machine Learning

Introducing Machine Learning
Author: Dino Esposito
Publisher: Microsoft Press
Total Pages: 616
Release: 2020-01-31
Genre: Computers
ISBN: 0135588383
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Master machine learning concepts and develop real-world solutions Machine learning offers immense opportunities, and Introducing Machine Learning delivers practical knowledge to make the most of them. Dino and Francesco Esposito start with a quick overview of the foundations of artificial intelligence and the basic steps of any machine learning project. Next, they introduce Microsoft’s powerful ML.NET library, including capabilities for data processing, training, and evaluation. They present families of algorithms that can be trained to solve real-life problems, as well as deep learning techniques utilizing neural networks. The authors conclude by introducing valuable runtime services available through the Azure cloud platform and consider the long-term business vision for machine learning. · 14-time Microsoft MVP Dino Esposito and Francesco Esposito help you · Explore what’s known about how humans learn and how intelligent software is built · Discover which problems machine learning can address · Understand the machine learning pipeline: the steps leading to a deliverable model · Use AutoML to automatically select the best pipeline for any problem and dataset · Master ML.NET, implement its pipeline, and apply its tasks and algorithms · Explore the mathematical foundations of machine learning · Make predictions, improve decision-making, and apply probabilistic methods · Group data via classification and clustering · Learn the fundamentals of deep learning, including neural network design · Leverage AI cloud services to build better real-world solutions faster About This Book · For professionals who want to build machine learning applications: both developers who need data science skills and data scientists who need relevant programming skills · Includes examples of machine learning coding scenarios built using the ML.NET library

Machine Learning with Microsoft Technologies

Machine Learning with Microsoft Technologies
Author: Leila Etaati
Publisher: Apress
Total Pages: 363
Release: 2019-06-12
Genre: Computers
ISBN: 1484236580
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Know how to do machine learning with Microsoft technologies. This book teaches you to do predictive, descriptive, and prescriptive analyses with Microsoft Power BI, Azure Data Lake, SQL Server, Stream Analytics, Azure Databricks, HD Insight, and more. The ability to analyze massive amounts of real-time data and predict future behavior of an organization is critical to its long-term success. Data science, and more specifically machine learning (ML), is today’s game changer and should be a key building block in every company’s strategy. Managing a machine learning process from business understanding, data acquisition and cleaning, modeling, and deployment in each tool is a valuable skill set. Machine Learning with Microsoft Technologies is a demo-driven book that explains how to do machine learning with Microsoft technologies. You will gain valuable insight into designing the best architecture for development, sharing, and deploying a machine learning solution. This book simplifies the process of choosing the right architecture and tools for doing machine learning based on your specific infrastructure needs and requirements. Detailed content is provided on the main algorithms for supervised and unsupervised machine learning and examples show ML practices using both R and Python languages, the main languages inside Microsoft technologies. What You'll Learn Choose the right Microsoft product for your machine learning solutionCreate and manage Microsoft’s tool environments for development, testing, and production of a machine learning projectImplement and deploy supervised and unsupervised learning in Microsoft products Set up Microsoft Power BI, Azure Data Lake, SQL Server, Stream Analytics, Azure Databricks, and HD Insight to perform machine learning Set up a data science virtual machine and test-drive installed tools, such as Azure ML Workbench, Azure ML Server Developer, Anaconda Python, Jupyter Notebook, Power BI Desktop, Cognitive Services, machine learning and data analytics tools, and more Architect a machine learning solution factoring in all aspects of self service, enterprise, deployment, and sharing Who This Book Is For Data scientists, data analysts, developers, architects, and managers who want to leverage machine learning in their products, organization, and services, and make educated, cost-saving decisions about their ML architecture and tool set.