Per augustus 2024 regelt de Europese AI Act welke toepassingen van kunstmatige intelligentie (AI) wel en niet zijn toegestaan, en aan welke voorwaarden AI-leveranciers en -gebruikers moeten voldoen bij het toepassen van de toegestane AI om compliant te worden en te blijven.

De AI Act is een verordening met risicocategorieën voor AI, bepalingen per risicocategorie en verplichtingen die afhangen van de rol van degene die de AI toepast. Hierdoor is de AI Act geen eenvoudige wet die je simpelweg...

AI-agents zijn niet langer toekomstmuziek: ze plannen agenda’s, verwerken documenten, ondersteunen klanten en coördineren processen. Steeds meer organisaties onderzoeken hoe ze deze slimme, taakgerichte systemen kunnen inzetten om werk te verlichten en waarde te creëren. Maar hoe breng je AI-agents van experiment naar praktijk?

In AI-agents in de praktijk leer je hoe je agents ontwikkelt die autonoom kunnen redeneren, beslissen en handelen – met behulp van frameworks als LangChain, Auto...

A Fortune magazine journalist draws on his expertise and extensive contacts among the companies and scientists at the forefront of artificial intelligence to offer dramatic predictions of AI's impact over the next decade, from reshaping our economy and the way we work, learn, and create to unknitting our social fabric, jeopardizing our democracy, and fundamentally altering the way we think.

Within the next five years, Jeremy Kahn predicts, AI will disrupt almost every industry and enterprise,...

Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Technical an...

A new edition of a graduate-level machine learning textbook that focuses on the analysis and theory of algorithms. This book is a general introduction to machine learning that can serve as a textbook for graduate students and a reference for researchers. It covers fundamental modern topics in machine learning while providing the theoretical basis and conceptual tools needed for the discussion and justification of algorithms. It also describes several key aspects of the application of these al...

Design clever algorithms that discover hidden patterns and draw responses from unstructured, unlabeled data. Key FeaturesBuild state-of-the-art algorithms that can solve your business' problemsLearn how to find hidden patterns in your dataRevise key concepts with hands-on exercises using real-world datasetsBook DescriptionStarting with the basics, Applied Unsupervised Learning with R explains clustering methods, distribution analysis, data encoders, and features of R that enable you to unders...

A substantially revised fourth edition of a comprehensive textbook, including new coverage of recent advances in deep learning and neural networks.

Learn the basics of Data Science through an easy to understand conceptual framework and immediately practice using RapidMiner platform. Whether you are brand new to data science or working on your tenth project, this book will show you how to analyze data, uncover hidden patterns and relationships to aid important decisions and predictions. Data Science has become an essential tool to extract value from data for any organization that collects, stores and processes data as part of its operations.

This book is ideal for business users, data analysts, business analysts, engineers, and analytics professionals and for anyone who works with data. You’ll be able to: Gain the necessary knowledge of different data science techniques to extract value from data. Master the concepts and inner workings of 30 commonly used powerful data science algorith...