Artificial Intelligence for Risk Management

· Business Expert Press
សៀវភៅ​អេឡិចត្រូនិច
162
ទំព័រ
មានសិទ្ធិ

អំពីសៀវភៅ​អេឡិចត្រូនិកនេះ

Artificial Intelligence (AI) for Risk Management is about using AI to manage risk in the corporate environment.

The content of this work focuses on concepts, principles, and practical applications that are relevant to the corporate and technology environments. The authors introduce AI and discuss the different types, capabilities, and purposes–including challenges.

With AI also comes risk. This book defines risk, provides examples, and includes information on the risk-management process. Having a solid knowledge base for an AI project is key and this book will help readers define the knowledge base needed for an AI project by developing and identifying objectives of the risk-knowledge base and knowledge acquisition for risk. This book will help you become a contributor on an AI team and learn how to tell a compelling story with AI to drive business action on risk.

អំពី​អ្នកនិពន្ធ

Archie Addo holds a PhD in computer information systems (CIS) with an emphasis in e‐commerce, cryptography, expert systems, and AI. He also has an executive data science certification from Johns Hopkins University, a certificate in contract law from Harvard Law School, Harvard University, and is a certified project management professional (PMP).

Srini Centhala is founder and chief architect of Absolut-e Data Com (a data company). Srini has provided expert consulting services to Fortune 100 companies for more than 20 years and is chief architect of the BizStats.ai Analytics platform. Specialties include business process re-engineering, business intelligence, senior data architect, machine learning, and AI to business data.

Muthu Shanmugam is chief technology officer at Absolut-e Data Com. Muthu has more than 20 years of experience. He holds a master of engineering from Anna University, India and works on Bizstats.ai to enable knowledge-based AI platforms using natural language processing (NLP), natural language understanding (NLU), application of machine learning, and AI.

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