Thema Maschinelles Lernen – alle Bücher

Marat Akhmet, Zakhira Nugayeva, Akylbek Zhamanshin, Madina Tleubergenova
Artificial Neural Networks

Mathematical chaos in neural networks is a powerful tool that reflects the world¿s complexity and has the potential to uncover the mysteries of the brain¿s intellectual activity. Through this monograph, t…

lieferbar innerhalb 2-3 Wochen

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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 …

lieferbar ab 30.10.2025.

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Alberta Albertella, Fernando Sansò
The Probabilistic Vision of the Physical World

This book investigates the relationship between empirical reality and theoretical modelling in Earth sciences, focusing on how empirical experiments and theoretical models interact. It explores the connec…

lieferbar innerhalb 2-3 Wochen

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Cristian Axenie, Meisam Akbarzadeh, Alexandru Stancu, Matteo Saveriano
Applied Antifragility in Technical Systems

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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Anupam Bagchi, Pramod Gupta
Essentials of Python for Artificial Intelligence and Machine Learning

This book introduces the essentials of Python for the emerging fields of Machine Learning (ML) and Artificial Intelligence (AI). The authors explore the use of Python's advanced module features and apply …

lieferbar innerhalb 2-3 Wochen

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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…

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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

SpringerBriefs in Computer Science

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 ab 1.12.2025.

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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

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

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Peter Boettke, Rosolino A. Candela, Tegan Lindstrom Truitt
The Socialist Calculation Debate

The collapse of communism in the Soviet Union and Eastern Europe delegitimized private property and central planning for socialism. However, the aspiration of achieving socialism's ends remains. This Elem…

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Peter Boettke, Rosolino A. Candela, Tegan Lindstrom Truitt
The Socialist Calculation Debate

The collapse of communism in the Soviet Union and Eastern Europe delegitimized private property and central planning for socialism. However, the aspiration of achieving socialism's ends remains. This Elem…

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…

sofort lieferbar

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

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 31.3.2026.

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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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…

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

lieferbar innerhalb 2-3 Wochen

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Ismaël Castillo
Bayesian Nonparametric Statistics

This up-to-date overview of Bayesian nonparametric statistics provides both an introduction to the field and coverage of recent research topics, including deep neural networks, high-dimensional models and…

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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…

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