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Building Responsible AI with Python. Learn to identify and mitigate bias with hands-on code examples Dr. Ali El-Sharif, Muhammad Rehman Zafar, Serg Masís , Nick Schmidt

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Building Responsible AI with Python. Learn to identify and mitigate bias with hands-on code examples Dr. Ali El-Sharif, Muhammad Rehman Zafar, Serg Masís , Nick Schmidt - okladka książki

Building Responsible AI with Python. Learn to identify and mitigate bias with hands-on code examples Dr. Ali El-Sharif, Muhammad Rehman Zafar, Serg Masís , Nick Schmidt - okladka książki

Autorzy:
Dr. Ali El-Sharif, Muhammad Rehman Zafar, Serg Masís, Nick Schmidt
Serie wydawnicze:
Hands-on
Wydawnictwo:
Packt Publishing (Z chęcią przeczytam książkę w języku polskim)
Ocena:
As we incorporate the next wave of AI-enabled products in high-stakes decisions, we need some level of assurance of the safety that we have come to expect from everyday products. Continuing the progress of using AI in high-stakes decisions requires trusting AI-enabled solutions to deliver their promised benefits while protecting the public from harm. Questions about the security, safety, privacy, and fairness of AI-enabled decisions need to be answered as a condition for deploying AI solutions at scale. This book is a guide that will introduce you to key concepts, use cases, tools, and techniques of the emerging field of Responsible AI. We will cover hands-on coding techniques to identify and measure bias. Measuring bias is not enough: we also need to explain and fix our models. This book outlines how to do this throughout the machine learning pipeline. By the end of this book, you will have mastered Python coding techniques of explaining machine learning models’ logic, measuring their fairness at the individual and group levels and monitor them in production environments to detect degradation in their accuracy or fairness.

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O autorach książki

Dr. Ali El-Sharif is a professor teaching Data Analytics and Cybersecurity. Dr. El-Sharif earned his Ph.D. in Information Systems at Nova Southeastern University, focusing on Explainable Artificial Intelligence. He also received Information Security from Nova Southeastern University, a Master of Business Administration (MBA), and a Bachelor of Computer Engineering from Wright State University. Dr. El-Sharif transitioned to academia after 20 years of being an industry practitioner, holding roles including software developer, solution architect, project manager, and management consultant.
Nicholas Schmidt started working in the field of responsible AI through his twenty years of experience working at the intersection of statistics, law, and regulation. He is currently the CEO of SolasAI and the AI Practice Leader at BLDS, LLC. Before that, Nicholas studied at the University of Chicago. In his work at SolasAI, he leads a team of data scientists and engineers building software that assesses whether there is evidence of bias or discrimination in an algorithm, and then provides alternative models that are both fairer and highly predictive. Nicholas believes that algorithms can be used as a force for good, but that responsible governance is necessary for that to happen

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