Online or onsite, instructor-led live ML.NET training courses demonstrate through interactive hands-on practice how to use ML.NET machine learning models to automatically derive projections from executed data analysis for enterprise applications..
ML.NET training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Onsite live ML.NET training can be carried out locally on customer premises in Vienna or in NobleProg corporate training centers in Vienna.
NobleProg -- Your Local Training Provider
NobleProg Wien
Modecenterstraße 22, Wien, Austria, 1030
Overview
Our training facilities are located at Modecenterstrasse 22 in Vienna. Our spaci...
Overview
Our training facilities are located at Modecenterstrasse 22 in Vienna. Our spacious training rooms offer optimal training conditions for your needs.
For questions and training registrations, please contact our company headquarters:
NobleProg Europe GmbH,
Kolonnenstr. 8
10827 Berlin
Deutschland
Directions
The NobleProg training facilities are conveniently located near the A23 motorway and the nearest subway station, within walking distance, is the Zippererstrasse station.
Parking spaces
There are parking spaces in the surrounding streets around our training rooms.
Local infrastructure
There are numerous restaurants within walking distance.
This instructor-led, live training in Vienna (online or onsite) is aimed at data scientists and developers who wish to use ML.NET machine learning models to automatically derive projections from executed data analysis for enterprise applications.
By the end of this training, participants will be able to:
Install ML.NET and integrate it into the application development environment.
Understand the machine learning principles behind ML.NET tools and algorithms.
Build and train machine learning models to perform predictions with the provided data smartly.
Evaluate the performance of a machine learning model using the ML.NET metrics.
Optimize the accuracy of the existing machine learning models based on the ML.NET framework.
Apply the machine learning concepts of ML.NET to other data science applications.
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