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Maschinelles Lernen - Grundlagen und Anwendungen

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Springer Nature
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9783662672761
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In diesem Fachbuch werden vorwiegend die Grundlagen des Maschinellen Lernens erlutert. Die Hauptthemen sind die mathematischen Grundlagen, Optimierungsmethoden und die ML-Algorithmen. Es wird zu jedem Kapitel mindestens eine Beispiel-bung durchgefhrt. Die bungen knnten durch Python-Code ergnzt werden. Zustzlich werden Aufgabenstellungen definiert, dies dient der Festigung des in dem jeweiligen Kapitel gelernten. Spezielle Anwendungen sollen ebenfalls dargestellt werden. Die Zielgruppe sind hauptschlich Studierende, welche sich in dieses Themengebiet einarbeiten mchten. Ingenieure knnen allerdings ebenfalls von diesem Fachbuch profitieren, da ein groer Schwerpunkt bei der Anwendung von ML liegt. Besonders die Verwendung in interdisziplinren Fachrichtungen wie der Regelungstechnik, Bildverarbeitung und der Chemie werden aufgezeigt.

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