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 Indiana can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
IN, Indianapolis - Lockerbie Marketplace
333 N. Alabama Street Suite 350, Indianapolis, united states, 46204
With its closeness to interstates and a dynamic global transportation infrastructure, as well as downtown amenities, the L...
With its closeness to interstates and a dynamic global transportation infrastructure, as well as downtown amenities, the Lockerbie Marketplace office on N. Alabama Street offers great accessibility. The office occupies the third floor of the smart Sears Building in the heart of Indianapolis’s historic district. Lockerbie Square is where many immigrants settled in the United States. Indianpolis (Indy) is an international city in Marion County that’s home to more than 500 overseas companies. It also has many vibrant sporting events including motoring mainstay, the Indy 500. Indianapolis lays claim to being one of the least expensive large cities in the US. The property is located near Lockerbie Chatham Arch and the main commercial hub of Massachusetts Avenue.
This instructor-led, live training in Indiana (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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