March 2019
Intermediate to advanced
368 pages
7h 53m
German
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KAPITEL 21
Trainierte Modelle speichern und laden
21.0Einführung
In den letzten 20 Kapiteln und rund 200 Rezepten haben wir gezeigt, wie man aus Rohdaten in Verbindung mit maschinellem Lernen gut funktionierende Vorhersagemodelle erzeugt. Damit sich unsere ganze Arbeit aber auch auszahlt, müssen wir tatsächlich irgendetwas tun mit unserem Modell –beispielsweise es in eine vorhandene Softwareanwendung integrieren. Um dieses Ziel zu erreichen, müssen wir in der Lage sein, unsere Modelle sowohl zu speichern, wenn das Training abgeschlossen ist, als auch wieder zu laden, wenn eine Anwendung sie benötigt. Diese Aufgaben stehen im Mittelpunkt unseres letzten Kapitels.
21.1Ein scikit-learn-Modell speichern und laden
Problem
Sie haben ein scikit-learn ...
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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.