Machine Learning Theory – alle Bücher

Prashad
Optimization Algorithms for Machine Learning: Theory and Practice

In the realm of machine learning, optimization algorithms play a pivotal role in refining models for optimal performance. These algorithms, ranging from classic gradient descent to advanced techniques lik…

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Kinky
Exploring Optimization Algorithms in Machine Learning: From Theory to Practice

Optimization algorithms in machine learning bridge theoretical foundations with practical applications, crucial for refining model performance. Techniques like gradient descent, stochastic gradient descen…

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Samuel Ackerman, Guy Barash, Onn Shehory, Orna Raz
Theory and Practice of Quality Assurance for Machine Learning Systems

This book is a self-contained introduction to engineering and testing machine learning (ML) systems. It systematically discusses and teaches the art of crafting and developing software systems that includ…

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Computer-Aided and Machine Learning-Driven Drug Design

The computer-aided drug design research field comprises several different knowledge areas, and often, researchers are only familiar or experienced with a small fraction of them. Indeed, pharmaceutical ind…

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Wilson Tsakane Mongwe, Tshilidzi Marwala, Rendani Mbuvha
Bayesian Machine Learning in Quantitative Finance

This book offers a comprehensive discussion of the Bayesian inference framework and demonstrates why this probabilistic approach is ideal for tackling the various modelling problems within quantitative fi…

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Pramod Gupta, Naresh Kumar Sehgal, John M. Acken
Introduction to Machine Learning with Security

This book provides an introduction to machine learning, security and cloud computing, from a conceptual level, along with their usage with underlying infrastructure. The authors emphasize fundamentals and…

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Yen-Wei Chen, Xiang Ruan, Rahul Kumar Jain
Recent Advances in Logo Detection Using Machine Learning Paradigms

This book presents the current trends in deep learning-based object detection framework with a focus on logo detection tasks. It introduces a variety of approaches, including attention mechanisms and doma…

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Robert Crowe, Hannes Hapke, Emily Caveness, Di Zhu
Machine Learning Production Systems

"Using machine learning for products, services, and critical business processes is quite different from using ML in an academic or research setting--especially for recent ML graduates and those movin…

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Steve Wilson
The Developer's Playbook for Large Language Model Security

"Large language models (LLMs) are not just shaping the trajectory of AI, they're also unveiling a new era of security challenges. This practical book takes you straight to the heart of these threats.…

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Juan Pablo Pardo-Guerra,
The Oxford Handbook of the Sociology of Machine Learning

This volume is the first comprehensive collection of essays exploring machine learning from a sociological perspective. It offers a thorough introduction to various forms of machine learning and features …

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SOFSEM 2025: Theory and Practice of Computer Science

This book constitutes the proceedings of the 50th International Conference on Current Trends in Theory and Practice of Computer Science, SOFSEM 2025, held in Bratislava, Slovak Republic, during January 20…

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SOFSEM 2025: Theory and Practice of Computer Science

This book constitutes the proceedings of the 50th International Conference on Current Trends in Theory and Practice of Computer Science, SOFSEM 2025, held in Bratislava, Slovak Republic, during January 20…

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Autonomous Cyber Resilience

Authoritative and highly comprehensive resource on the latest research and strategies to develop cyber resilience in any network systemAutonomous Cyber Resilience presents key research contributions in th…

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Quantum Computing

This book provides readers with the current state-of-the-art research and technology on quantum computing. The authors provide design paradigms of quantum computing. Topics covered include multi-programmi…

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