Introduction to Prescriptive AI: A Primer for Decision Intelligence Solutioning with Python

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 biases can 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 ForData Scientists and Machine Learning Engineers, as well as business professionals who want to understand how AI-driven decision intelligence can help grow their business.

獲得對於指導性人工智慧（prescriptive AI）的工作知識，包括其歷史以及目前和未來的趨勢。本書將幫助您評估不同的以人工智慧為基礎的預測分析技術，並通過實際案例幫助您將決策智能融入您的業務工作流程中。

本書以介紹決策智能為開端，並提供了對於指導性人工智慧以及如何將其融入不同業務策略和框架的見解。接著，您將了解不同的決策智能方法論以及如何實施它們，以及每種方法的優點和限制。更深入地探討，作者們將引導您如何進行模擬並解讀結果。全書的一個章節專門介紹了如何使用各種應用程式將決策智能流程和結果嵌入到您的業務工作流程中。最後，本書探討了人類容易產生的不同認知偏見，以及如何通過結合機器和人類智能來消除這些偏見。

閱讀完本書後，您將了解指導性人工智慧的工具和技術，並準備將其融入到您的業務工作流程中。

您將學到什麼：
- 使用Python實施完整的決策智能應用程式
- 利用工具、技術和方法論進行指導性人工智慧
- 通過實際案例了解指導性人工智慧在不同領域的應用
- 解讀結果並將其整合到您的決策過程中

本書適合對象：
- 數據科學家和機器學習工程師，以及希望了解以人工智慧為基礎的決策智能如何幫助業務增長的業務專業人士。

Akshay R. Kulkarni is an artificial intelligence (AI) and machine learning (ML) evangelist and a thought leader. He has consulted several Fortune 500 and global enterprises to drive AI and data science-led strategic transformations. He is a Google developer, an author, and a regular speaker at major AI and data science conferences (including the O'Reilly Strata Data & AI Conference and Great International Developer Summit (GIDS)) . He is a visiting faculty member at some of the top graduate institutes in India. In 2019, he was featured as one of India's "top 40 under 40" data scientists. In his spare time, Akshay enjoys reading, writing, coding, and helping aspiring data scientists. He lives in Bangalore with his family.

Adarsha Shivananda is a data science and MLOps leader. He is working on creating world-class MLOps capabilities to ensure continuous value delivery from AI. He aims to build a pool of exceptional data scientists within and outside organizations to solve problems through training programs. He always wants to stay ahead of the curve. Adarsha has worked extensively in the pharma, healthcare, CPG, retail, and marketing domains. He lives in Bangalore and loves to read and teach data science.

Avinash Manure is a seasoned Machine Learning Professional with 10+ years of experience building, deploying, and maintaining state-of-the-art machine learning solutions across different industries. He has 6+ years of experience leading and mentoring high-performance teams in developing ML systems catering to different business requirements. He is proficient in deploying complex machine learning and statistical modeling algorithms/techniques for identifying patterns and extracting valuable insights for key stakeholders and organizational leadership.

Akshay R. Kulkarni 是一位人工智慧（AI）和機器學習（ML）的倡導者和思想領袖。他曾為多家財富500強和全球企業提供諮詢服務，推動AI和數據科學引領的戰略轉型。他是一位Google開發者、作家，並經常在主要的AI和數據科學會議上發表演講（包括O'Reilly Strata Data＆AI Conference和Great International Developer Summit（GIDS））。他是印度一些頂尖研究所的客座教師。2019年，他被列為印度「40位40歲以下頂尖數據科學家」之一。在閒暇時間，Akshay喜歡閱讀、寫作、編程和幫助有志成為數據科學家的人。他與家人一起居住在班加羅爾。

Adarsha Shivananda 是一位數據科學和MLOps（機器學習運營）領導者。他致力於建立世界一流的MLOps能力，以確保從AI中持續提供價值。他的目標是通過培訓計劃在組織內外建立一支優秀的數據科學家團隊，解決問題。他始終希望保持領先。Adarsha在製藥、醫療保健、消費品、零售和營銷領域有豐富的工作經驗。他居住在班加羅爾，喜歡閱讀和教授數據科學。

Avinash Manure 是一位經驗豐富的機器學習專業人士，擁有10多年的經驗，在不同行業建立、部署和維護最先進的機器學習解決方案。他有6年多領導和指導高效團隊開發滿足不同業務需求的機器學習系統的經驗。他擅長部署複雜的機器學習和統計建模算法/技術，用於識別模式並為關鍵利益相關者和組織領導層提取有價值的見解。