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. Hsinchu onsite live Random Forest trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
The Hsinchu Wishun centre
HSR Hsinchu Station District Lots, 6/F, No.46 and No.47 in ShiHsin Section, Hsinchu, taiwan, 30274
The Hsinchu Wishun centre is located in the commercial area of Hsinchu THSR district. It only takes 1 minute walk to Hsinchu ...
The Hsinchu Wishun centre is located in the commercial area of Hsinchu THSR district. It only takes 1 minute walk to Hsinchu HSR station which is connected to the centre building and Train Neiwan line. With its convenient transport connectivity, it is also easy to access through National Highway No.1 and Expressway to Hsinchu Science Park (8km) and Hsinchu CBD (15km ).
The centre is located at one of the very few grade A buildings in Hsinchu. The newly constructed building is with abundant local amenities, including restaurants, retail shops, recreation facilities and a hotel. Nearby parks and hotels include Shuizhen Forest Park and Hsinchu Sheraton hotel. Surrounded by hi-tech companies and high end residential communities, the location is a new hub for companies that are looking to grow and start their business in Hsinchu. Regus Hsinchu Wishun centre offers flexible workplace solutions to accommodate needs of all types and sizes with comprehensive services at a reasonable price.
This instructor-led, live training in Hsinchu (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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