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 New Jersey or in NobleProg corporate training centers in New Jersey.
NobleProg -- Your Local Training Provider
NJ, Totowa - Riverview Drive
999 Riverview Drive, Totowa, united states, 07512
Totowa, NJ - The venue is located on the corner of Riverview Dr and Commerce Way.
NJ, Princeton - Overlook Business Center
100 Overlook Center, Princeton, united states, 08540
The venue is located just off Highway 1, in the vicinity of the American Red Cross of Central New Jersey and Wells Fargo Bank...
The venue is located just off Highway 1, in the vicinity of the American Red Cross of Central New Jersey and Wells Fargo Bank.
NJ, Newark - One Gateway Business Center
One Gateway Center Suite 2600, Newark, united states, 07102
Located in New Jersey, it is next to the Seton Hall University Law School and the Prudential Center, and a block from the pre...
Located in New Jersey, it is next to the Seton Hall University Law School and the Prudential Center, and a block from the prestigious New Jersey Performing Arts Center. The building is connected by covered walkway to Newark Penn making New York a short commute by PATH and giving good access to Boston and Washington DC.
This instructor-led, live training in New Jersey (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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