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. Manila onsite live Random Forest trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Joy Nostalg
ADB Avenue, Pasig, Philippines
Modern, conducive and equipped for our training courses
Manila Enterprise Makati
28th Floor, Tower 2, The Enterprise Centre, Manila, Philippines, 1226
Manila's Enterprise Makati Centre is at the heart of the business and finance district in one of the most popular commercial buildings in Makati City. This business centre overlooks the skyscrapers of Makati and from the board rooms there are stunning views of the historic Manila Bay. Described as 'The Business Building Designed for Building Business', it is in a neo-classical landmark twin tower building with magnificently designed facilities, a range of retail and leisure facilities and seven levels of underground parking accommodating 1,200 vehicles. Makati is the country's undisputed financial centre and commercial hub and is home to the headquarters of the 40 per cent of the top 1,000 multinational and local corporations. The city has the most developed telecommunications infrastructure in the country. Transport links are excellent and the Ninoy Aquino International Airport is just five kilometres away.
This instructor-led, live training in Manila (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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