Machine Learning with Dynamics 365 and Power Platform
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Machine Learning with Dynamics 365 and Power Platform: The Ultimate Guide to Apply Predictive Analytics

Machine Learning with Dynamics 365 and Power Platform: The Ultimate Guide to Apply Predictive Analytics


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About the Book

Apply cutting-edge AI techniques to your Dynamics 365 environment to create new solutions to old business problems In Machine Learning with Dynamics 365 and Power Platform: The Ultimate Guide to Apply Predictive Analytics, an accomplished team of digital and data analytics experts delivers a practical and comprehensive discussion of how to integrate AI Builder with Dataverse and Dynamics 365 to create real-world business solutions. It also walks you through how to build powerful machine learning models using Azure Data Lake, Databricks, Azure Synapse Analytics. The book is filled with clear explanations, visualizations, and working examples that get you up and running in your development of supervised, unsupervised, and reinforcement learning techniques using Microsoft machine learning tools and technologies. These strategies will transform your business verticals, reducing costs and manual processes in finance and operations, retail, telecommunications, and manufacturing industries. The authors demonstrate: What machine learning is all about and how it can be applied to your organization's Dynamics 365 and Power Platform Projects The creation and management of environments for development, testing, and production of a machine learning project How adopting machine learning techniques will redefine the future of your ERP/CRM system Perfect for Technical Consultants, software developers, and solution architects, Machine Learning with Dynamics 365 and Power Platform is also an indispensable guide for Chief Technology Officers seeking an intuitive resource for how to implement machine learning in modern business applications to solve real-world problems.

Table of Contents:
Foreword vii Preface ix Acknowledgments xi About the Authors xiii Chapter 1: Dynamics 365, Power Platform, and Machine Learning 1 Introduction to Dynamics 365 1 Introduction to Power Platform 6 What Is Machine Learning: How Has It Evolved? 11 Definition of Machine Learning 12 Chapter 2: Artificial Intelligence and Pre- Built Machine Learning in Dynamics 365 33 Azure AI Platform 33 Azure Machine Learning Service 41 Knowledge Mining 67 Chapter 3: ML/AI Features and Their Applications in Dynamics 365 71 Customer Insights 71 Customer Service Insights 77 Sales Insights 83 Product Insights 95 Virtual Agent for Customer Service in Dynamics 365 96 Artificial Intelligence in Power Apps with AI Builder 99 What Is Mixed Reality? 102 Chapter 4: Dynamics 365 and Custom ML Models Using Azure ML 107 Azure Machine Learning 108 Azure Machine Learning Studio 115 Azure Machine Learning Service 146 Chapter 5: Deep Dive in Machine Learning Custom Models 149 Azure CLI Extension 149 Visual Studio Code 153 Chapter 6: Machine Learning with Dynamics 365 Use Cases 161 ml for Finance 162 Demand Forecasting 190 Connected Store 192 ml for Human Resources Management 195 Machine Learning at the Workplace 200 Afterword 205 Index 207

About the Author :
AURELIEN CLERE is a Microsoft MVP, Global Solution Architect with 10 years of experience in the Dynamics world (ERP, CRM). He is a speaker and organizes weekly webinars. VINNIE BANSAL is an independent Dynamics 365 Business Advisor. He liaises between business and IT teams and serves as technical advisor to clients in assigned subject areas.


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Product Details
  • ISBN-13: 9781119771319
  • Publisher: John Wiley & Sons Inc
  • Publisher Imprint: Standards Information Network
  • Language: English
  • Sub Title: The Ultimate Guide to Apply Predictive Analytics
  • ISBN-10: 1119771315
  • Publisher Date: 29 Dec 2021
  • Binding: Digital (delivered electronically)
  • No of Pages: 240


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Machine Learning with Dynamics 365 and Power Platform: The Ultimate Guide to Apply Predictive Analytics
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Machine Learning with Dynamics 365 and Power Platform: The Ultimate Guide to Apply Predictive Analytics
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