By Andreas C. Müller,Sarah Guido,Kristian Rother
Mit Python und der scikit-learn-Bibliothek erarbeiten Sie sich alle Schritte, die für eine erfolgreiche Machine-Learning-Anwendung notwendig sind. Die Autoren Andreas Müller und Sarah Guido konzentrieren sich bei der Verwendung von Machine-Learning-Algorithmen auf die praktischen Aspekte statt auf die Mathematik dahinter. Wenn Sie zusätzlich mit den Bibliotheken NumPy und matplotlib vertraut sind, hilft Ihnen dies, noch mehr aus diesem instructional herauszuholen.
Das Buch zeigt Ihnen:
- grundlegende Konzepte und Anwendungen von computing device Learning
- Vor- und Nachteile weit verbreiteter maschineller Lernalgorithmen
- wie sich die von laptop studying verarbeiteten Daten repräsentieren lassen und auf welche Aspekte der Daten Sie sich konzentrieren sollten
- fortgeschrittene Methoden zur Auswertung von Modellen und zum Optimieren von Parametern
- das Konzept von Pipelines, mit denen Modelle verkettet und Arbeitsabläufe gekapselt werden
- Arbeitsmethoden für Textdaten, insbesondere textspezifische Verarbeitungstechniken
- Möglichkeiten zur Verbesserung Ihrer Fähigkeiten in den Bereichen computer studying und information Science
Dieses Buch ist eine fantastische, tremendous praktische Informationsquelle für jeden, der mit desktop studying in Python starten möchte – ich wünschte nur, es hätte schon existiert, als ich mit scikit-learn anfing!
Hanna Wallach, Senior Researcher, Microsoft Research
Read Online or Download Einführung in Machine Learning mit Python: Praxiswissen Data Science (Animals) (German Edition) PDF
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