Thema Maschinelles Lernen – alle Bücher, Seite 6

Hermann Selchow
Is man still relevant? A provocation (Extended Version)

Is man still relevant? A provocation - technological evolution and human existenceThe world is changing rapidly - algorithms are making decisions, machines are taking on tasks that were once reserved for …

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Massimiliano Salerno
Social Media Is Dead

Social media didn't die overnight - it died slowly, while no one was paying attention. And now AI has finished the job.While the world is drowning in synthetic content, cloned personalities, fake engageme…

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Massimiliano Salerno
Social Media Is Dead

Social media didn't die overnight - it died slowly, while no one was paying attention. And now AI has finished the job.While the world is drowning in synthetic content, cloned personalities, fake engageme…

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

Probability and Frequency.- 2. The Sources of Stochasticity.- 3. Statistical Inference: The Theory of Estimation.- 4. Statistical Inference: Model Verification.- 5. Finite vs Infinite, Discrete vs Continu…

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Thomas Schmid, Wolfgang Hildesheim, Taras Holoyad
Managing and Understanding Artificial Intelligence: From Classical to Generative AI

Artificial Intelligence (AI) is taking over the world, becoming an essential part of our daily lives. Self-driving cars, medical diagnoses, robotic processes, chatbots, and urban planning are just a few e…

lieferbar ab 8.3.2026.

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Terrence Sejnowski
The Deep Learning Revolution

How deep learning---from Google Translate to driverless cars to personal cognitive assistants---is changing our lives and transforming every sector of the economy.The deep learning revolution has brought …

lieferbar ab 3.2.2026.

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Yue Song, Thomas Anderson Keller, Nicu Sebe, Max Welling
Structured Representation Learning

This book introduces approaches to generalize the benefits of equivariant deep learning to a broader set of learned structures through learned homomorphisms. In the field of machine learning, the idea of …

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Roshan Srivastav, Purna C. Nayak
Applications of Machine Learning in Hydroclimatology

Applications of Machine Learning in Hydroclimatology is a comprehensive exploration of the transformative potential of machine learning for addressing critical challenges in water resources management. Th…

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Predrag S. Stanimirovi¿, Yimin Wei, Shuai Li, Dimitrios Gerontitis
Generalized Matrix Inversion: A Machine Learning Approach

This book presents a comprehensive exploration of the dynamical system approach in numerical linear algebra, with a special focus on computing generalized inverses, solving systems of linear equations, an…

lieferbar ab 2.1.2026.

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Du¿an Stipanovi¿
Difference Equations and Machine Learning

This book presents in-depth explanations of well-known and recognized behaviors of neural networks in machine learning. In addition, the author provides novel technical analyses of behaviors of discrete-t…

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N. Sukumar
Navigating Molecular Networks

This book delves into the foundational principles governing the treatment of molecular networks and "chemical space"-the comprehensive domain encompassing all physically achievable molecules-fro…

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Jian-Qiao Sun
Random Vibration with Machine Learning Method

The book presents the theoretical foundation of random vibration of dynamic systems and new machine learning methods for the analysis of linear and nonlinear random vibration problems. This is the first b…

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Gaurav Suri, Jay McClelland
The Emergent Mind

'Excellent' - Geoffrey Hinton, the 'godfather of AI' and Nobel laureate in Physics'An indispensable guide to both ourselves and the coming age of AI' - Mustafa Suleyman, bestselling co-author of The Comin…

lieferbar ab 19.2.2026.

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Richard Susskind
How To Think About AI

Revealing the unfolding story of Artificial Intelligence, Richard Susskind presents a short non-technical guide that challenges us to think differently about AI. Susskind brings AI out of computing labora…

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Joe Suzuki
Graphical Models and Causal Discovery with R

Beginning with a gentle introduction to causal discovery and the foundations of probability and statistics, this textbook is written in a highly pedagogical way. By uniting probability theory, statistical…

lieferbar ab 4.3.2026.

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Xiaoming Tao, Yiping Duan, Zhijin Qin, Danlan Huang
Wireless Multimedia Computational Communications

This book discusses the evolving designs and applications of multimedia content delivery and focuses on computing-based methods. It offers readers an in-depth understanding of how computational resources …

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Julian Togelius, Georgios N. Yannakakis
Artificial Intelligence and Games

This second edition of the 2018 textbook captures significant developments in AI and gaming over the past 7 years, incorporating advancements in computer vision, reinforcement learning, deep learning, and…

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Jakub M. Tomczak
Deep Generative Modeling

This first comprehensive book on models behind Generative AI has been thoroughly revised to cover all major classes of deep generative models: mixture models, Probabilistic Circuits, Autoregressive Models…

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Chen-Tse Tsai, Shyam Upadhyay, Dan Roth
Multilingual Entity Linking

This book focuses on Entity Discovery and Linking (EDL), which is the problem of identifying concepts and entities, disambiguating them, and grounding them to one or more knowledge bases (KBs). The author…

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Leslie Valiant
The Importance of Being Educable

Why you should worry less about AI and more about what makes us humanWe are at a crossroads in history. If we hope to share our planet successfully with one another and the AI systems we are creating, we …

lieferbar ab 19.5.2026.

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