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. Penang Island onsite live Random Forest trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
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 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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