November 2023
Intermediate to advanced
576 pages
13h 30m
German
Content preview from Handbuch Data Science mit PythonBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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KAPITEL 39
Hyperparameter und Modellvalidierung
Im letzten Kapitel haben Sie das grundlegende Rezept für die Anwendung überwachter Machine-Learning-Modelle kennengelernt:
- Auswahl des Modells.
- Auswahl der Hyperparameter des Modells.
- Anpassen des Modells an die Trainingsdaten.
- Anwendung des Modells auf neue Daten zur Vorhersage der Labels.
Die ersten beiden Punkte – Auswahl von Modell und Hyperparametern – dürften wohl am meisten dazu beitragen, die Tools und Verfahren effektiv einsetzen zu können. Wir müssen überprüfen (validieren) können, ob unser Modell und die Hyperparameter für die vorliegenden Daten gut geeignet sind, um fundierte Entscheidungen treffen zu können. Das hört sich vielleicht einfach an, aber es gibt einige Stolpersteine, die ...
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I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.