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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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- More about Machine Learning with Dynamics 365 and Power Platform - The Ultimate Guide to Apply Predictive Analytics
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.
Weight: 500g
Dimension: 161 x 239 x 24 (mm)
ISBN-13: 9781119771296
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