Random Forest Training in Swansea

Random Forest Training in Swansea

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 Swansea or in NobleProg corporate training centres in Swansea.

NobleProg -- Your Local Training Provider

Swansea - Princess Way

Princess House
Princess Way
Swansea SA1 3LW
United Kingdom
,
See map: Google Maps
GB
Swansea - Princess Way
Learn Random Forest in our training center in Swansea. The Princess House Centre is located in the heart of Swansea with panoramic views over the city, Swansea Bay and the Gower area of outstanding natural beauty. These offices are in a prime location and have recently undergone a major refurbishment. Swansea is an inspiring place to do business in a superb natural environment. It is Wales' second largest city and the regional shopping, leisure, cultural, education and administrative centre for south west Wales. In recent years, it has experienced... Read more

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Random Forest Course Events - Swansea

Random Forest Course Outlines in Swansea

Course Name
Duration
Overview
Course Name
Duration
Overview
14 hours
This instructor-led, live training in Swansea (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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