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Springer Maschinelles Lernen: Die Grundlagen

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Description

Maschinelles Lernen (ML) ist zu einem alltäglichen Element in unserem Leben und zu einem Standardwerkzeug für viele Bereiche der Wissenschaft und Technik geworden. Um ML optimal nutzen zu können, ist es wichtig, die zugrunde liegenden Prinzipien zu verstehen. In diesem Buch wird ML als die rechnerische Umsetzung des wissenschaftlichen Prinzips betrachtet. Dieses Prinzip besteht darin, ein Modell eines gegebenen datenerzeugenden Phänomens kontinuierlich anzupassen, indem eine Form des Verlustes, der durch seine Vorhersagen entsteht, minimiert wird. Das Buch schult den Leser darin, verschiedene ML-Anwendungen und -Methoden in drei Komponenten (Daten, Modell und Verlust) aufzuschlüsseln, und hilft ihm so, aus dem riesigen Angebot an vorgefertigten ML-Methoden auszuwählen. Der Drei-Komponenten-Ansatz des Buches erlaubt eine einheitliche und transparente Darstellung verschiedener ML-Techniken. Wichtige Methoden zu Regularisierung, zum Schutz der Privatsphäre und zur Erklärbarkeit von ML-Methoden sind Spezialfälle dieses Drei-Komponenten-Ansatz.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
14 February 2024
Listed Since
30 September 2023

Barcode

No barcode data available

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