Thema Maschinelles Lernen – alle Bücher, Seite 4

Gang Liu, Eric Inae, Meng Jiang
Deep Learning for Polymer Discovery

This book presents a comprehensive range of topics in deep learning for polymer discovery, from fundamental concepts to advanced methodologies. These topics are crucial as they address critical challenges…

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Pedro A. López-García, Denisse L. Argote
Determining Provenance from Compositional Data

Traditionally, classical multivariate statistical methods have been applied to relate cultural materials recovered at archaeological sites to their respective raw material sources. However, when reviewing…

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Pedro A. López-García, Denisse L. Argote
Determining Provenance from Compositional Data

Traditionally, classical multivariate statistical methods have been applied to relate cultural materials recovered at archaeological sites to their respective raw material sources. However, when reviewing…

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Sidi Lu, Weisong Shi
Vehicle Computing

Over the past century, vehicles have predominantly functioned as a means of transportation. However, as vehicular computation and communication capacities continue to expand, it is anticipated that upcomi…

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Man Luo, Tejas Gokhale, Neeraj Varshney, Yezhou Yang
Advances in Multimodal Information Retrieval and Generation

This book provides an extensive examination of state-of-the-art methods in multimodal retrieval, generation, and the pioneering field of retrieval-augmented generation. The work is rooted in the domain of…

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Monia Lupparelli, Giovanni Maria Marchetti, Claudia Tarantola
Regression Graph Models for Categorical Data

This book consolidates knowledge on regression chain graph models, often referred to as regression graph models, with a particular emphasis on their parameterizations and inference for the analysis of cat…

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Sarit Maitra
Non-Linearity in Econometric Modeling, Vol. 1

Nonlinear models are indispensable in modern finance, yet their reliance on numerical root-finding methods introduces layers of complexity that demand careful attention. This textbook offers a comprehensi…

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Bernhard Metzger
KI verstehen, anwenden, profitieren

KI verstehen, anwenden, profitieren - Praxiswissen, Prompts und Strategien für den erfolgreichen KI-Einsatz im Alltag und Beruf ist dein interaktiver Begleiter in die Welt der Künstlichen Intelligenz. Du …

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Bernhard Metzger
KI verstehen, anwenden, profitieren

KI verstehen, anwenden, profitieren - Praxiswissen, Prompts und Strategien für den erfolgreichen KI-Einsatz im Alltag und Beruf ist dein interaktiver Begleiter in die Welt der Künstlichen Intelligenz. Du …

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Sean Meyn
Control Systems and Reinforcement Learning

"A high school student can create deep Q-learning code to control her robot, without any understanding of the meaning of "deep" or "Q", or why the code sometimes fails. This book …

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Rudy Milani
Advanced Automation for Comprehensible Causal Explanations of Reinforcement Learning Agents

This thesis introduces Auto-BENEDICT, a novel, fully automated methodology designed to generate human-comprehensible causal explanations for model-free Reinforcement Learning (RL) agents. The system addre…

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Laurence Moroney,
PyTorch für KI und ML

Animals

PyTorch kompetent nutzen, KI-Modelle erfolgreich bauenEin praxis- und codeorientierter Guide für Python-Entwickler*innenAnwendungen mit KI und ML entwickeln, ohne fortgeschrittene Mathematik- oder Theorie…

lieferbar ab 30.4.2026.

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Laura Mostert, Roy Lindelauf, Chiara Pulice, Marnix Provoost
Machine Learning Techniques to Predict Terrorist Attacks

Chapter 1 Introduction.- Chapter 2 Jama'at Nasr al-Islam wal Muslimin (JNIM).- Chapter 3 Temporal Probabilistic Rules and Policy Computation Algorithms.- Chapter 4 Abduction and Release of Abductees.- Cha…

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John Paul Mueller, Luca Massaron
Machine Learning For Dummies

The most human-friendly book on machine learningSomewhere buried in all the systems that drive artificial intelligence, you'll find machine learning-the process that allows technology to build knowledge b…

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Lisette Nieves, Noel S. Anderson, Becca Huntting
Working for a Future

This book builds on the success of "Working to Learn" (Palgrave Macmillan, 2020) by focusing on the future of work and how young people, especially low-income young people and young people of co…

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David Pacheco Aznar, Esteban Vanegas, Miquel Noguer I Alonso
Large Language Models

This book provides a technically rigorous yet accessible guide to Large Language Models (LLMs), charting their evolution from academic research projects into critical infrastructure for industries as dive…

lieferbar ab 4.4.2026.

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Stefan Papp, Jeannette Gorzala, Gerald A. Hahn, Georg Langs
Handbuch Data Science und KI

Umfassender Überblick über die verschiedenen Anwendungsbereiche von Data Science und KI Fallbeispiele aus der Praxis Praktische Beispielen, die Ihnen helfen, einfache Datenanalyseprojekte durchzuführen Ne…

lieferbar ab 12.6.2026.

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Quinn
The Power of Recognizing Intent: From Social Skills to AI Safety

Human interaction hinges on our ability to understand the intent behind words and actions. A seemingly innocuous statement can take on a hostile or playful tone depending on the speaker's intent. Likewise…

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Zhiwei Qin (Tony), Xiaocheng Tang, Qingyang Li, Hongtu Zhu
Reinforcement Learning in the Ridesharing Marketplace

This book provides a comprehensive overview of reinforcement learning for ridesharing applications. The authors first lay out the fundamentals of the ridesharing system architectures and review the basics…

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Ognjen Radi¿i¿-Aberger
Optimisation and Control of Engineering Change Schedules in the Automotive Industry with Metaheuristics and Machine Learning

Adaptation and change are imperative for products and companies to remain competitive. Managing these changes, however, is increasingly difficult and requires thorough planning and management. Especially …

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