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Gesamtkatalog

Catalogue complet

The book discusses various partitioning strategies tailored for traditional machine learning algorithms. This book is a vital resource, illuminating the path towards unlocking the full potential of partitioning in shaping the future of AI technologies.

Guggari S: Advances in Partitioning
Techniques

Advances in Partitioning Techniques

A prospective towards Artificial Intelligence

1. Introduction to partitioning techniques 2. Partitioning techniques for deep learning techniques 3. Graph-based partitioning techniques 4. Partitioning techniques for Big Data 5. Partitioning techniques for edge computing

Deep Learning in Computer Vision

Creativity in the Age of AI

What Art Is Now

A comprehensive, up-to-date introduction to active inference and the free energy principle for an engineering-focused audience. Active inference, which uses machine learning to model brain function and behavior, emerged from decades of cross-disciplinary research in computational neuroscience, resulting in a vast literature but no unifying treatment. Filling this gap, Sanjeev Namjoshi provides comprehensive coverage of the foundational material needed to understand and navigate this fast-moving field from first principles. Using a simple, conversational style free of proofs, lemmas, and theorems, Namjoshi brings together theory and technical material in one self-contained text. The book begins with an explanation of the general statistical framework used in active inference models that describes the relationship between artificial agents and their environments. It then introduces fundamental concepts in machine learning and statistics and connects them to the active inference perspective. Featuring worked examples, simulations, and detailed walkthroughs of concepts, this user-friendly text aims to expand the readership of active inference to an engineering-focused audience.&nbsp; <ul><li>Provides a one-stop-shop for understanding the foundations and applications of active inference and the free energy principle </li><li>Makes a complex, interdisciplinary subject accessible to students and professionals beyond the neurosciences</li><li>Covers discrete and continuous state-space formulations of active inference as well as state-of-the-art extensions to base active inference methods</li><li>Features extensive appendices and supplemental resources</li></ul>

Principles, Algorithms, and Applications of the Free Energy Principle for Engineers

Fundamentals of Active Inference

Images in The Age of Heat

Medium Hot

Artificial Intelligence and Machine Learning in Data Science and Analytics

Data-Driven Modeling

Medical Robots and Devices: New Developments and Advances

AI and Data Science in Medical Research focuses on the integration of AI and data science into medical research, highlighting their impact on drug discovery, medical imaging, diagnostics, and genomic medicine. The book addresses the acceleration of therapeutic compound discovery and optimization of drug development pipelines through AI. The volume also discusses advancements in medical imaging, including early disease detection and neuroimaging. Additionally, it covers the application of AI in genomic medicine, offering insights into personalized treatment strategies. The volume concludes with an examination of AI's role in public health surveillance, particularly in disease detection and epidemiological research.

AI and Data Science in Medical Research

Practical Bioinformatics

Multi-Agent Control Systems

Connected Diagnoses: IoT, Healthcare, and Digital Forensics investigates the complex intersection of IoT, healthcare, and digital forensics. This book explores the intricate relationships between these fields, with a focus on cybersecurity, patient data ethics, and challenges in IoT investigations. This book advances knowledge on leveraging IoT securely to enhance patient care and digital forensic analysis, providing significant insights from experts along with practical guidance for those operating at the crossroads of these critical disciplines. The book helps professionals grasp, adapt to, and capitalize on the interconnected nature of emerging technologies to ensure ethics, security, and safety. It is a comprehensive resource that benefits researchers and practitioners seeking to understand the convergence of medical technology, interconnected devices, and digital forensics.

IoT, Healthcare, and Digital Forensics

Connected Diagnoses

Machine Learning For Dummies

Smart Charging Infrastructures

Advances in Partitioning Techniques

Weitere Titel zum Thema