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This book explores the application of the complex relationship between concept drift and cutting-edge large language models to address the problems and opportunities in navigating changing data landscapes.
This book provides a guide to working efficiently with larger-than-memory datasets using the arrow R package. You'll learn how to overcome... Læs mere
This handbook addresses how smart operations, management, and healthcare can be used to detect and analyze supply chain problems, business problems, and diseases. It also discusses the underlying methodologies and related security concerns.
The topic of AAL is already a part of the curriculum in many universities and institutes, and this book will... Læs mere
A Concise Introduction to Machine Learning uses mathematics as the common language to explain a variety of machine learning concepts from basic principles and... Læs mere
This book discusses the relevance of probabilistic supervised learning, to the pursuit of automated and reliable prediction of an... Læs mere
Discusses various solutions for the diagnosis of patients with the help of automated processes... Læs mere
Intelligent Manufacturing delves into the challenges of incorporating AI-driven frameworks and standards into the... Læs mere
This book offers an in-depth exploration of explainable learner models, presenting theoretical foundations and practical applications in... Læs mere
Author Doug Gray shares the most important lessons he has learned over the course of his 30+ year career in analytics and technology. Readers will witness... Læs mere
This book is written for the many health professionals who are regularly frustrated by elegant but ambiguous descriptions of results of data... Læs mere