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. Abu Dhabi onsite live ML.NET trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
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Park Rotana Complex
Abu Dhabi, United Arab Emirates
Situated within the Park Complex and adjacent to TwoFour54 and Khalifa Park. Park Rotana is 15 minutes drive from Abu Dhabi I...
Situated within the Park Complex and adjacent to TwoFour54 and Khalifa Park. Park Rotana is 15 minutes drive from Abu Dhabi International Airport and Yas Island.
Driving directions from Abu Dhabi International Airport:
Drive towards Abu Dhabi by highway No. E 10, Keep driving straight after passing the “Al Raha mall”. Follow the signage “Sheikh Zayed Bridge” to drive through the bridge, Keep in the right lane when you finish the bridge. You are now driving on “Salam / Eastern” road. Take the exit “Khalifa Park & Ministries Complex” from extreme right lane to make a “U turn” over the underpass, Follow the signal “Park Rotana Complex” and take right to the roundabout. After it, turn left in the roundabout and drive straight until you reach Park Rotana.
This instructor-led, live training in Abu Dhabi (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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