November 2016
Intermediate to advanced
424 pages
11h 9m
German
book
Machine Learning mit Python - Das Praxis-Handbuch für Data Sience, Predictive Analytics und Deep Learning
by Sebastian Raschka
Content preview from Machine Learning mit Python - Das Praxis-Handbuch für Data Sience, Predictive Analytics und Deep Learning
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Kapitel 6: Bewährte Verfahren zur Modellbewertung und Hyperparameter-Abstimmung
In den vorangegangenen Kapiteln haben Sie die grundlegenden Lernalgorithmen für die Klassifizierung kennengelernt und erfahren, wie Sie die Daten aufbereiten können, bevor die Algorithmen damit gefüttert werden. Nun ist es an der Zeit, sich mit den bewährten Verfahren zur Entwicklung guter Lernmodelle durch die Feinabstimmung der Algorithmen und die Bewertung der Leistung zu befassen.
Die Themen in diesem Kapitel sind:
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Verfahrensfehlerfreie Bewertung der Leistung eines Modells
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Typische bei Lernalgorithmen auftretende Schwierigkeiten
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Feinabstimmung von Lernmodellen
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Bewertung von Vorhersagemodellen anhand verschiedener Leistungskriterien
6.1 Arbeitsabläufe ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
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.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
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.