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

Aurelien Clere

ISBN 10: 1119771293 / ISBN 13: 9781119771296

Edité par Wiley Jan 2022, 2022

Neuware - Apply cutting-edge AI techniques to your Dynamics 365 environment to create new solutions to old business problemsIn 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 systemPerfect 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. N° de réf. du vendeur 9781119771296

Synopsis :

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.

À propos de l?auteur:

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.

Détails bibliographiques

Titre : Machine Learning with Dynamics 365 and Power...
Éditeur : Wiley Jan 2022
Date d'édition : 2022
Reliure : Buch
Etat : Neu