Introduction to Prescriptive AI -  Akshay Kulkarni,  Avinash Manure,  Adarsha Shivananda

Introduction to Prescriptive AI (eBook)

A Primer for Decision Intelligence Solutioning with Python
eBook Download: PDF
2023 | 1. Auflage
XVI, 194 Seiten
Apress (Verlag)
978-1-4842-9568-7 (ISBN)
Systemvoraussetzungen
46,99 inkl. MwSt
  • Download sofort lieferbar
  • Zahlungsarten anzeigen
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 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.

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.


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 LearnImplement full-fledged decision intelligence applications using PythonLeverage the tools, techniques, and methodologies for prescriptive AIUnderstand how prescriptive AI can be used in different domains through practical examplesInterpret results and integrate them into your decision makingWho 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.
Erscheint lt. Verlag 26.6.2023
Zusatzinfo XVI, 194 p. 17 illus.
Sprache englisch
Themenwelt Mathematik / Informatik Informatik Programmiersprachen / -werkzeuge
Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Schlagworte decision intelligence • Decision Making • Deep learning • machine learning • Prescriptive AI • Prescriptive Analytics • Python
ISBN-10 1-4842-9568-4 / 1484295684
ISBN-13 978-1-4842-9568-7 / 9781484295687
Haben Sie eine Frage zum Produkt?
PDFPDF (Wasserzeichen)
Größe: 3,5 MB

DRM: Digitales Wasserzeichen
Dieses eBook enthält ein digitales Wasser­zeichen und ist damit für Sie persona­lisiert. Bei einer missbräuch­lichen Weiter­gabe des eBooks an Dritte ist eine Rück­ver­folgung an die Quelle möglich.

Dateiformat: PDF (Portable Document Format)
Mit einem festen Seiten­layout eignet sich die PDF besonders für Fach­bücher mit Spalten, Tabellen und Abbild­ungen. Eine PDF kann auf fast allen Geräten ange­zeigt werden, ist aber für kleine Displays (Smart­phone, eReader) nur einge­schränkt geeignet.

Systemvoraussetzungen:
PC/Mac: Mit einem PC oder Mac können Sie dieses eBook lesen. Sie benötigen dafür einen PDF-Viewer - z.B. den Adobe Reader oder Adobe Digital Editions.
eReader: Dieses eBook kann mit (fast) allen eBook-Readern gelesen werden. Mit dem amazon-Kindle ist es aber nicht kompatibel.
Smartphone/Tablet: Egal ob Apple oder Android, dieses eBook können Sie lesen. Sie benötigen dafür einen PDF-Viewer - z.B. die kostenlose Adobe Digital Editions-App.

Buying eBooks from abroad
For tax law reasons we can sell eBooks just within Germany and Switzerland. Regrettably we cannot fulfill eBook-orders from other countries.

Mehr entdecken
aus dem Bereich
der Praxis-Guide für Künstliche Intelligenz in Unternehmen - Chancen …

von Thomas R. Köhler; Julia Finkeissen

eBook Download (2024)
Campus Verlag
38,99
Wie du KI richtig nutzt - schreiben, recherchieren, Bilder erstellen, …

von Rainer Hattenhauer

eBook Download (2023)
Rheinwerk Computing (Verlag)
24,90