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 trainings in Namur can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Namur, Hotel de Ville
NobleProg Namur, Rue de Fer, 48 , Namur, Belgium, 5000
Namur is a French-speaking city in Belgium, capital of Wallonia since 1986, and capital of the province of Namur. Occupied...
Namur is a French-speaking city in Belgium, capital of Wallonia since 1986, and capital of the province of Namur. Occupied since the Neolithic period, the confluence of the Sambre and the Meuse saw the birth of the Roman city at the beginning of our era. Former stronghold of the Counts of Namur, attached to the house of Luxembourg and then to the Habsburg Empire, the citadel of Namur was the focus of many sieges over the years. Despite the damage suffered by the conflicts, the city retains a rich movable and immovable heritage. Today the regional capital, the city is the seat of the Parliament of Wallonia, the Walloon Government and the Public Service of Wallonia, but also the host city of the International Francophone Film Festival, the fairground arts festival Namur in May, the Festival Verdur Rock.
This instructor-led, live training in Namur (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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