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. Onsite live Random Forest training can be carried out locally on customer premises in New Jersey or in NobleProg corporate training centers in New Jersey.
NobleProg -- Your Local Training Provider
NJ, Totowa - Riverview Drive
999 Riverview Drive, Totowa, united states, 07512
Totowa, NJ - The venue is located on the corner of Riverview Dr and Commerce Way.
NJ, Princeton - Overlook Business Center
100 Overlook Center, Princeton, united states, 08540
The venue is located just off Highway 1, in the vicinity of the American Red Cross of Central New Jersey and Wells Fargo Bank...
The venue is located just off Highway 1, in the vicinity of the American Red Cross of Central New Jersey and Wells Fargo Bank.
NJ, Newark - One Gateway Business Center
One Gateway Center Suite 2600, Newark, united states, 07102
Located in New Jersey, it is next to the Seton Hall University Law School and the Prudential Center, and a block from the pre...
Located in New Jersey, it is next to the Seton Hall University Law School and the Prudential Center, and a block from the prestigious New Jersey Performing Arts Center. The building is connected by covered walkway to Newark Penn making New York a short commute by PATH and giving good access to Boston and Washington DC.
This instructor-led, live training in New Jersey (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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