Online or onsite, instructor-led live Random Forest training courses demonstrate through interactive hands-on practice how to use Random Forest to build machine learning algorithms for large datasets.
Random Forest 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. San Francisco Bay Area onsite live Random Forest trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
CA, Sunnyvale - Downtown Sunnyvale
640 W California Ave Suite 210, Sunnyvale, united states, 94086
The Sunnyvale center is located one block from Caltrain rail station and provides easy access to Central Expressway and High...
The Sunnyvale center is located one block from Caltrain rail station and provides easy access to Central Expressway and Highway 101.
It is in walking distance to the city's downtown district, featuring numerous restaurants, shops, and businesses, as well as a short drive from San Jose International Airport.
CA, San Francisco - Golden Gate
75 Broadway, San Francisco , united states, 94111
With its fabulous arched windows, the 75 Broadway office, located in the heart of Jackson Square, is designed to impress. Sit...
With its fabulous arched windows, the 75 Broadway office, located in the heart of Jackson Square, is designed to impress. Situated at Golden Gateway Commons on the second floor of this unique campus-style building, it overlooks the green terrain's of Sydney Walton Park with the famous waterfront piers behind. This enviable location is a short walk from public transport and just blocks away from the Embarcadero and the ferry building, as well as a host of convenient amenities.
This instructor-led, live training in San Francisco Bay Area (online or onsite) is aimed at data scientists and software engineers who wish to use Random Forest to build machine learning algorithms for large datasets.
By the end of this training, participants will be able to:
Set up the necessary development environment to start building machine learning models with Random forest.
Understand the advantages of Random Forest and how to implement it to resolve classification and regression problems.
Learn how to handle large datasets and interpret multiple decision trees in Random Forest.
Evaluate and optimize machine learning model performance by tuning the hyperparameters.
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