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 4: Gut geeignete Trainingsdatenmengen: Datenvorverarbeitung
Die Qualität der Daten sowie der Umfang der darin enthaltenen Informationen sind entscheidende Faktoren, die festlegen, wie gut ein Lernalgorithmus daraus lernen kann. Daher ist es absolut unverzichtbar, eine Datensammlung zu untersuchen und vorzuverarbeiten, bevor wir einen Lernalgorithmus damit füttern. In diesem Kapitel werden wir wichtige Verfahren zur Datenvorverarbeitung erörtern, die es ermöglichen sollen, gut funktionierende Lernmodelle zu entwickeln.
Die Themen in diesem Kapitel:
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Unvollständige Werte aus der Datensammlung entfernen und fehlende Werte zuweisen
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Aufbereitung kategorialer Daten für den Lernalgorithmus
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Auswahl der für die Modellentwicklung maßgeblichen ...
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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.