Unsupervised Learning – alle Bücher

Stefan Selle
Data Science Training - Supervised Learning

Dieses Lehrbuch erklärt auf narrative und direkte Weise die wichtigen Zusammenhänge zwischen Data Science, Künstlicher Intelligenz und anderen Disziplinen und Domänen wie Datenschutz und Ethik, mit Fokus …

lieferbar innerhalb 2-3 Wochen

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Giovanni Cerulli
Fundamentals of Supervised Machine Learning

This book presents the fundamental theoretical notions of supervised machine learning along with a wide range of applications using Python, R, and Stata. It provides a balance between theory and applicati…

lieferbar innerhalb 2-3 Wochen

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Vaibhav Verdhan
Models and Algorithms for Unlabelled Data

Discover all-practical implementations of the key algorithms and models for handling unlabeled data. Full of case studies demonstrating how to apply each technique to real-world problems. In Models and Al…

lieferbar ab 1.10.2025.

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Signal Processing Driven Machine Learning Techniques for Cardiovascular Data Processing

Signal Processing Driven Machine Learning Techniques for Cardiovascular Data Processing features recent advances in machine learning coupled with new signal processing-based methods for cardiovascular dat…

lieferbar in mind. 4 Wochen

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Taeho Jo
Deep Learning Foundations

This book provides a conceptual understanding of deep learning algorithms. The book consists of the four parts: foundations, deep machine learning, deep neural networks, and textual deep learning. The fir…

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Discovery Science

The two-volume set LNAI 15243 + 15244 constitutes the proceedings of the 27th International Conference on Discovery Science, DS 2024, which took place in Pisa, Italy, during October 14-16, 2024.The 53 ful…

lieferbar innerhalb 2-3 Wochen

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Gilles Pagès, Harald Luschgy
Marginal and Functional Quantization of Stochastic Processes

Vector Quantization, a pioneering discretization method based on nearest neighbor search, emerged in the 1950s primarily in signal processing, electrical engineering, and information theory. Later in the …

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Johannes Lederer
A First Course in Statistical Learning

This textbook introduces the fundamental concepts and methods of statistical learning. It uses Python and provides a unique approach by blending theory, data examples, software code, and exercises from be…

lieferbar innerhalb 2-3 Wochen

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Discovery Science

The two-volume set LNAI 15243 + 15244 constitutes the proceedings of the 27th International Conference on Discovery Science, DS 2024, which took place in Pisa, Italy, during October 14-16, 2024.The 53 ful…

lieferbar innerhalb 2-3 Wochen

Buch

Khanh Luong, Richi Nayak
Multi-aspect Learning

This book offers a detailed and comprehensive analysis of multi-aspect data learning, focusing especially on representation learning approaches for unsupervised machine learning. It covers state-of-the-ar…

lieferbar innerhalb 2-3 Wochen

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Advanced Analytics and Learning on Temporal Data

This book constitutes the refereed proceedings of the 9th ECML PKDD workshop on Advanced Analytics and Learning on Temporal Data, AALTD 2024, held in Vilnius, Lithuania, during September 9-13, 2024.The 8 …

lieferbar innerhalb 2-3 Wochen

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Federated Learning in the Age of Foundation Models - FL 2024 International Workshops

This LNAI volume constitutes the post proceedings of International Federated Learning Workshops such as follows:FL@FM-WWW 2024, FL@FM-ICME 2024, FL@FM-IJCAI 2024 and FL@FM-NeurIPS 2024. This LNAI volume f…

lieferbar innerhalb 2-3 Wochen

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Artificial Intelligence for Smart Manufacturing and Industry X.0

This book offers a foundational understanding of smart manufacturing (SM) and introduces effective AI methods tailored for smart manufacturing, including supervised, unsupervised, and reinforcement learni…

lieferbar innerhalb 2-3 Wochen

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Artificial Intelligence and Machine Learning in Healthcare

Artificial Intelligence and Machine Learning in Healthcare discusses the potential of groundbreaking technologies on the delivery of care. A lot have been said about how artificial intelligence and machin…

lieferbar ab 1.9.2025.

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