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 Barranquilla or in NobleProg corporate training centers in Barranquilla.
NobleProg -- Your Local Training Provider
Barranquilla - Buro 51
Calle 94 #51B-43, Barranquilla, colombia
Buro 51 is a first class mix use complex which incorporates a class “A” office building and a 4 star Movich Hotel. Ground floor offers a variety of retail shops and amenities, and the building offeres unobstructed views of Barranquilla.
The center is located in Buenavista Trade Area, which is the most upscale and exclusive of the city with easy access to main highways to the international airport and port. Offers:
Fully equipped offices, ready to start working
Meeting rooms and videoconferencing studio
Regus IT high speed internet access
Administrative support on request
Major transport link - City/town center
Break-out areas
Elevate your presence with distinction at this prestigious office space situated in an enviable locale nestled between downtown and the Magdalena River. Green Towers boasts proximity to local enterprises and major banks, with convenient access to bus stops for seamless commuting.
This instructor-led, live training in Barranquilla (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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