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 Iowa or in NobleProg corporate training centers in Iowa.
NobleProg -- Your Local Training Provider
IA, Des Moines - Hub Tower
699 Walnut Street, Des Moines, united states, 50309
The venue is located in the Hub Tower, right next door to Burger King and in the vicinity of the Kaleidoscope at the Hub Mall...
The venue is located in the Hub Tower, right next door to Burger King and in the vicinity of the Kaleidoscope at the Hub Mall.
IA, Johnston - Des Moines - Foxboro Square
6165 Northwest 86th Street, Des Moines, united states, 50131
The venue is located in the neighboorhood of the Community Choice Credit Union and Iowa Orthodontic Solutions, just in front ...
The venue is located in the neighboorhood of the Community Choice Credit Union and Iowa Orthodontic Solutions, just in front of the Green Meadows West Gazebo.
NE, Omaha – Linden Place
14301 First National Bank Parkway, Suite 100, Omaha, united states, 68154
The venue is located next to the First National Bank Park & Ride bus stop in the same building as Midwest Retirement Advisors...
The venue is located next to the First National Bank Park & Ride bus stop in the same building as Midwest Retirement Advisors and Principal Financial Group.
This instructor-led, live training in Iowa (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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