Deep Learning And GenAI – alle Bücher online kaufen

Roland Schwaiger, Joachim Steinwendner
Neuronale Netze programmieren mit Python

Neuronale Netze stehen im Mittelpunkt, wenn es um Künstliche Intelligenz und Machine Learning geht. Sie revolutionieren Bild- und Spracherkennung, Spiele-KIs und vieles mehr. Zum Glück lassen sich die gen…

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Lasha Abzianidze, Lisa Bylinina, Denis Paperno
Semantics and Deep Learning

This Element covers the interaction of two research areas: linguistic semantics and deep learning. It focuses on three phenomena central to natural language interpretation: reasoning and inference; compos…

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Lasha Abzianidze, Lisa Bylinina, Denis Paperno
Semantics and Deep Learning

This Element covers the interaction of two research areas: linguistic semantics and deep learning. It focuses on three phenomena central to natural language interpretation: reasoning and inference; compos…

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Deep Ray, Assad A. Oberai, Orazio Pinti
Deep Learning and Computational Physics

The main objective of this book is to introduce a student who is familiar with elementary math concepts to select topics in deep learning. It exploits strong connections between deep learning algorithms a…

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Zekâi ¿En
Shallow and Deep Learning Principles

This book discusses Artificial Neural Networks (ANN) and their ability to predict outcomes using deep and shallow learning principles. The author first describes ANN implementation, consisting of at least…

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Deep Learning Theory and Applications

The two-volume set CCIS 2171 and 2172 constitutes the refereed best papers from the 5th International Conference on Deep Learning Theory and Applications, DeLTA 2024, which took place in Dijon, France, du…

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Deep Learning Theory and Applications

The two-volume set CCIS 2171 and 2172 constitutes the refereed papers from the 5th INternational Conference on Deep Learning Theory and Applications, DeLTA 2024, which took place in Dijon, France, during …

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Charu C. Aggarwal
Neural Networks and Deep Learning

This book covers both classical and modern models in deep learning. The primary focus is on the theory and algorithms of deep learning. The theory and algorithms of neural networks are particularly import…

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Innovations in Machine and Deep Learning

In recent years, significant progress has been made in achieving artificial intelligence (AI) with an impact on students, managers, scientists, health personnel, technical roles, investors, teachers, and …

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Deep Learning in Genetics and Genomics

Deep Learning in Genetics and Genomics: Vol. 2 (Advanced Applications) delves into the Deep Learning methods and their applications in various fields of studies, including genetics and genomics, bioinform…

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Deep Learning in Genetics and Genomics

Deep Learning in Genetics and Genomics vol. 1, Foundations and Applications, the intersection of deep learning and genetics opens up new avenues for advancing our understanding of the genetic code, gene r…

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Deep Learning and Other Soft Computing Techniques

This book focuses on the use of artificial intelligence (AI) and computational intelligence (CI) in medical and related applications. Applications include all aspects of medicine: from diagnostics (includ…

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Deep Learning for Earth Observation and Climate Monitoring

Deep Learning for Earth Observation and Climate Monitoring bridges the gap between deep learning and the Earth sciences, offering cutting-edge techniques and applications that are transforming our underst…

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Kwang Hun Kim, Ju Song Kim, Song Il Ri
Application of data decomposition and deep learning technique

Water pollution is one of the most serious environmental problems worldwide. Accurate forecast of water quality is of great importance since it can provide useful information for the managers to minimize …

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Shirui Wang, Jiefu Chen, Xuqing Wu, Wenyi Hu
Deep Learning for Seismic Data Enhancement and Representation

Seismic imaging is a key component of subsurface exploration, and it depends on a high-quality seismic data acquisition system with effective seismic processing algorithms. Seismic data quality concerns v…

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Deep Learning Techniques for Automation and Industrial Applications

This book provides state-of-the-art approaches to deep learning in areas of detection and prediction, as well as future framework development, building service systems and analytical aspects in which arti…

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Johannes Jahn
Order Analysis, Deep Learning, and Connections to Optimization

This book introduces readers to order analysis and various aspects of deep learning, and describes important connections to optimization, such as nonlinear optimization as well as vector and set optimizat…

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Deep Reinforcement Learning and Its Industrial Use Cases

This book serves as a bridge connecting the theoretical foundations of DRL with practical, actionable insights for implementing these technologies in a variety of industrial contexts, making it a valuable…

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Rabia Riad, Frederic Ros
Feature and Dimensionality Reduction for Clustering with Deep Learning

This book presents an overview of recent methods of feature selection and dimensionality reduction that are based on Deep Neural Networks (DNNs) for a clustering perspective, with particular attention to …

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Deep Learning for Advanced X-ray Detection and Imaging Applications

This book provides a comprehensive overview of the latest advances in applying Artificial Intelligence (AI) to advanced X-ray imaging, with a particular focus on its medical applications. Readers will dis…

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