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 Penang Island or in NobleProg corporate training centers in Penang Island.
NobleProg -- Your Local Training Provider
Bayan Lepas, iDEAL
73-3-1, Ideal@The One, Jalan , Kuala Lumpur, malaysia, 11950
The iDEAL Bayan Baru is located in the township near Bayan Lepas, Penang International Airport and also the second Penang Bri...
The iDEAL Bayan Baru is located in the township near Bayan Lepas, Penang International Airport and also the second Penang Bridge. The Building is located in Bayan Baru CBD, and within Bayan Lepas Free Trade Zone. Due to its proximity to the free trade zone that is home to many MNCs, this South-West District is one of the preferred retail/shopping destination s for working professionals, families, visitors and MICE (meeting, incentive, convention, exhibition).
Bayan Baru as part of the Penang Cybercity phase 1, has been identified as a key focus market in Malaysia’s development plan for 2015. It has easy access to corporate offices, restaurants, banks and many more amenities. Our center provide flexible, fully-equipped office workspaces for businesses large and small, branch or sales offices, agencies and consultancies, with comprehensive services at a reasonable price.
This instructor-led, live training in Penang Island (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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