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Learn Microsoft Fabric

You're reading from   Learn Microsoft Fabric A practical guide to performing data analytics in the era of artificial intelligence

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Product type Paperback
Published in Feb 2024
Publisher Packt
ISBN-13 9781835082287
Length 338 pages
Edition 1st Edition
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Authors (2):
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Bradley Schacht Bradley Schacht
Author Profile Icon Bradley Schacht
Bradley Schacht
Arshad Ali Arshad Ali
Author Profile Icon Arshad Ali
Arshad Ali
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Table of Contents (19) Chapters Close

Preface 1. Part 1: An Introduction to Microsoft Fabric FREE CHAPTER
2. Chapter 1: Overview of Microsoft Fabric and Understanding Its Different Concepts 3. Chapter 2: Understanding Different Workloads and Getting Started with Microsoft Fabric 4. Part 2: Building End-to-End Analytics Systems
5. Chapter 3: Building an End-to-End Analytics System – Lakehouse 6. Chapter 4: Building an End-to-End Analytics System – Data Warehouse 7. Chapter 5: Building an End-to-End Analytics System – Real-Time Analytics 8. Chapter 6: Building an End-to-End Analytics System – Data Science 9. Part 3: Administration and Monitoring
10. Chapter 7: Monitoring Overview and Monitoring Different Workloads 11. Chapter 8: Administering Fabric 12. Part 4: Security and Developer Experience
13. Chapter 9: Security and Governance Overview 14. Chapter 10: Continuous Integration and Continuous Deployment (CI/CD) 15. Part 5: AI Assistance with Copilot Integration
16. Chapter 11: Overview of AI Assistance and Copilot Integration 17. Index 18. Other Books You May Enjoy

Building an End-to-End Analytics System – Data Science

Almost every organization on the planet is on its journey of taking advantage of innovation and the advancements of artificial intelligence (AI) and machine learning (ML). However, the challenge is that there are so many products and libraries to consider that you will spend most of your time trying to figure out ways of doing it right and promptly.

Microsoft Fabric has been designed from the ground up for the era of ML and AI to drive business value for your organization.

In this chapter, you will learn about the data science capabilities in Fabric by following the end-to-end data science life cycle and building an ML model, all the way from data ingestion to cleansing, feature engineering, training, and operationalizing models. We will cover the following topics:

  • Understanding the data science project development life cycle and how Fabric’s capabilities help in each of the stages
  • Data and storage...
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