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. Kuala Lumpur onsite live Random Forest trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Kuala Lumpur KL Sentral
1 Sentral, Level 16, Jalan , Kuala Lumpur, malaysia, 50470
The 1 Sentral Centre is located in the northwest corner of Kuala Lumpur Sentral, a prime location in the heart of the city. A...
The 1 Sentral Centre is located in the northwest corner of Kuala Lumpur Sentral, a prime location in the heart of the city. Although 1 Sentral is just outside the central business district, Kuala Lumpur Sentral is known as a transportation hub and as one of the designated Multimedia Supercorridor (MSC) locations. A Government designated zone, the MSC is designed to leapfrog Malaysia into the information and knowledge age. The zone aims to attract companies with tax breaks and facilities such as high speed internet and proximity to the local international airport. 1 Sentral is a 30-storey office tower covering an acre and is equipped with facilities such as mini auditorium, gymnasium and recreational area. Its architecture has integrated a variety of design techniques that make it eco-friendly and aesthetically-pleasing. Restaurants, top hotels and shopping centres are all within a five- to 10-minute walk from the centre
This instructor-led, live training in Kuala Lumpur (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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