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. Liverpool onsite live ML.NET trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Liverpool
Horton House, Liverpool, united kingdom, L2 3PF
This business centre is situated in Exchange Flags, a beautifully restored landmark property at the heart of Liverpool's r...
This business centre is situated in Exchange Flags, a beautifully restored landmark property at the heart of Liverpool's rejuvenated business district. This is Liverpool's best office address. The elegance of the original architecture has been matched by a sympathetic yet stylish refurbishment, which has set a benchmark for Grade A office accommodation across the city. Two office buildings flank an impressive bustling open square, which is enclosed by Liverpool Town Hall. Occupiers so far include legal, accountancy, consulting and property firms and The Ministry of Defence. The World Heritage waterfront, a 10,000-seater arena and a conference centre are on the doorstep as well as the Liverpool One shopping and leisure complex. Not since its days as the foremost port in the world has Liverpool witnessed development activity at current levels. This is a city that means business and is attracting investment and visitors from across the world.
This instructor-led, live training in Liverpool (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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