Thema Maschinelles Lernen – alle Bücher

Sanad Aburass, Ibrahim Aljarah
Classical Machine Learning

The field of Artificial Intelligence (AI) has rapidly transformed in recent years, with Machine Learning being now one of its most impactful and widely applied branches. From intelligent recommendation sy…

Erscheint bald

Buch

Jay Alammar, Maarten Grootendorst,
Praxisbuch Large Language Models

Animals

Alle Werkzeuge und Techniken für die praktische Arbeit mit LLMsDas Handbuch für das intuitive Verständnis von LLMs: Mit zahlreichen Visualisierungen, die Konzepte schnell zugänglich machenThemen sind die …

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Daniel Alpay
Exercises in Applied Mathematics

Chapman Mathematical Notes

This text presents a collection of mathematical exercises with the aim of guiding readers to study topics in statistical physics, equilibrium thermodynamics, information theory, and their various connecti…

lieferbar innerhalb 2-3 Wochen

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Massih-Reza Amini
Advanced Supervised and Semi-supervised Learning

Cognitive Technologies

Machine learning is one of the leading areas of artificial intelligence. It concerns the study and development of quantitative models that enable a computer to carry out operations without having been exp…

lieferbar innerhalb 2-3 Wochen

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Cosmin Anitescu, Somdatta Goswami, Timon Rabczuk, Xiaoying Zhuang
Scientific Machine Learning with Engineering Applications

Studies in Systems, Decision and Control

This book equips readers with a rigorous and practical framework for solving complex engineering problems directly from governing equations using modern machine learning techniques. It bridges established…

lieferbar ab 24.4.2026.

Buch

Cristian Axenie, Meisam Akbarzadeh, Michail A. Makridis, Matteo Saveriano
Applied Antifragility in Technical Systems

SpringerBriefs in Computer Science

The book purpose is to build a foundational knowledge base by applying antifragile system design, analysis, and development in technical systems, with a focus on traffic engineering, robotics, and control…

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Ying Bai
AI Foundations and Applications with MATLAB

This textbook provides fundamentals and practical skills on AI foundations and applications with two MATLAB programming modes. It includes twelve chapters with detailed introductions for the foundation kn…

lieferbar innerhalb 2-3 Wochen

Buch

Grey Ballard, Tamara G Kolda
Tensor Decompositions for Data Science

Aimed at students in mathematics, computer science, statistics, engineering, and physical and life sciences, this book introduces the foundations of tensor decompositions, a data analysis methodology ubiq…

lieferbar innerhalb 1-2 Wochen

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Rubén Ballester, Carles Casacuberta, Sergio Escalera
Topological Data Analysis for Neural Networks

This book offers a comprehensive presentation of methods from topological data analysis applied to the study of neural network structure and dynamics. Using topology-based tools such as persistent homolog…

lieferbar innerhalb 2-3 Wochen

Buch

Steven F. Barrett
Arduino V: Machine Learning, 2ed

Synthesis Lectures on Digital Circuits & Systems

This book is about the Arduino microcontroller and the Arduino concept. The visionary Arduino represented a new innovation in microcontroller hardware in 2005, the concept of open source hardware, making …

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Max Bennett
A Brief History of Intelligence

Bridges the gap between AI and neuroscience by telling the story of how the brain came to be.'I found this book amazing' Daniel Kahneman, Winner of the Nobel Prize in Economics and bestselling author of T…

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Deepshikha Bhati, Fnu Neha, Angela Guercio, Md Amiruzzaman
A Beginner's Guide to Generative AI

Synthesis Lectures on Computer Science

This book is the essential guide for anyone curious about AI's creative power. In the rapidly evolving landscape of artificial intelligence, generative AI stands out as one of the most transformative tech…

lieferbar innerhalb 2-3 Wochen

Buch

Ulisses Braga-Neto
Fundamentals of Pattern Recognition and Machine Learning

This book is a concise but thorough introduction to the tools commonly used in pattern recognition and machine learning, including classification, dimensionality reduction, regression, and clustering, as …

lieferbar innerhalb 2-3 Wochen

Buch

Steven L. Brunton, J. Nathan Kutz
Data-Driven Science and Engineering

Data-driven discovery is revolutionizing how we model, predict, and control complex systems. Now with Python and MATLAB®, this textbook trains mathematical scientists and engineers for the next generation…

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Jeremy Budd, Yves van Gennip
Differential Equations and Variational Methods on Graphs

Cambridge Monographs on Applied and Computational Mathematics

The burgeoning field of differential equations on graphs has experienced significant growth in the past decade, propelled by the use of variational methods in imaging and by its applications in machine le…

lieferbar ab 30.4.2026.

Buch

Andriy Burkov,
Language Models kompakt

Der schnellste Weg, um die Mechanismen von LLMs zu verstehenDieses Buch ist eine sehr komprimierte und gleichzeitig gut verständliche Einführung in die Entwicklung von Large Language ModelsIdeal für alle,…

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Harvard Business
HBR's 10 Must Reads on AI, Updated and Expanded

How to stay ahead in a world transformed by AI.If you read nothing else on artificial intelligence, read this book. We've chosen a new selection of current and classic Harvard Business Review articles tha…

lieferbar ab 12.5.2026.

Buch

Dany Cajas
Advanced Portfolio Optimization

This book is an innovative and comprehensive guide that provides readers with the knowledge about the latest trends, models and algorithms used to build investment portfolios and the practical skills nece…

lieferbar innerhalb 2-3 Wochen

Buch

Jeff Calder, Peter J. Olver
Linear Algebra, Data Science, and Machine Learning

This text provides a mathematically rigorous introduction to modern methods of machine learning and data analysis at the advanced undergraduate/beginning graduate level. The book is self-contained and req…

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Buch

Antonio Candelieri, Andrea Ponti, Francesco Archetti
Multiple Information Source Bayesian Optimization

SpringerBriefs in Optimization

The book provides a comprehensive review of multiple information sources and multi-fidelity Bayesian optimization, specifically focusing on the novel "Augmented Gaussian Process" methodology. Th…

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