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 Trojmiasto or in NobleProg corporate training centers in Trojmiasto.
NobleProg -- Your Local Training Provider
Gdynia
Hotel Nadmorski, Ejsmonda 2, Gdynia, Poland, 81-409
The training room is located just 3 kilometers from the PKP/PKS Station in Gdynia, making it easily accessible for participants traveling by train or bus. Additionally, it is only 400 meters away from the bus stop, facilitating access even for those using public transportation. It is equipped with necessary training tools such as a projector, screen, and flipchart, providing comfortable conditions for both participants and the trainer.
Gdańsk
Hotel Fahrenheit, Grodzka 19, Gdańsk, Poland, 80-841
The training room is located in the very heart of the picturesque Gdansk Old Town, making the surroundings not only inspiring but also exceptionally attractive for participants. Within close proximity, you can find the railway and bus stations, facilitating arrival for those traveling by both train and bus. Additionally, the airport and port are also within reach, making this location convenient for individuals coming from distant places, both domestically and internationally.
This instructor-led, live training in Trojmiasto (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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