Gain a working knowledge of prescriptive AI, its history, and its current and future trends. This book will help you evaluate different AI-driven predictive analytics techniques and help you incorporate decision intelligence into your business workflow through real-world examples. The book kicks off with an introduction to decision intelligence and provides insight into prescriptive AI and how it can be woven into various business strategies and frameworks. You'll then be introduced to different decision intelligence methodologies and how to implement them, along with advantages and limitations of each. Digging deeper, the authors then walk you through how to perform simulations and interpret the results. A full chapter is devoted to embedding decision intelligence processes and outcomes into your business workflow using various applications. The book concludes by exploring different cognitive biases humans are prone to, and how those biasescan be eliminated by combining machine and human intelligence. Upon completing this book, you will understand prescriptive AI, tools, and techniques and will be ready to incorporate them into your business workflow. What You Will Learn

Implement full-fledged decision intelligence applications using Python
Leverage the tools, techniques, and methodologies for prescriptive AI
Understand how prescriptive AI can be used in different domains through practical examples
Interpret results and integrate them into your decision making

Who This Book Is For Data Scientists and Machine Learning Engineers, as well as business professionals who want to understand how AI-driven decision intelligence can help grow their business.

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Yes, you can access Introduction to Prescriptive AI by Akshay Kulkarni,Adarsha Shivananda,Avinash Manure in PDF and/or ePUB format, as well as other popular books in Informatique & Intelligence artificielle (IA) et sémantique. We have over one million books available in our catalogue for you to explore.

Information

Publisher

Apress

Year

2023

ISBN

9781484295687

Topic

Informatique

Subtopic

Intelligence artificielle (IA) et sémantique

Cover
Front Matter
1. Decision Intelligence Overview
2. Decision Intelligence Requirements
3. Decision Intelligence Methodologies
4. Interpreting Results from Different Methodologies
5. Augmenting Decision Intelligence Results into the Business Workflow
6. Actions, Biases, and Human-in-the-Loop
7. Case Studies
Back Matter