Random Forest Training in Bradford

Random Forest Training in Bradford

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 trainings in Bradford can be carried out locally on customer premises or in NobleProg corporate training centres.

NobleProg -- Your Local Training Provider

Bradford - Carlisle Business Centre

Carlisle Business Centre
60 Carlisle Road
Bradford, WYK BD8 8BD
United Kingdom
,
See map: Google Maps
West Yorkshire GB
Bradford - Carlisle Business Centre
Learn Random Forest in our training center in Bradford. Carlisle Business Centre is a not for private profit organisation, driven by a dedicated workforce, that's supported by a voluntary board of directors. We operate as a social enterprise that donates its generated profit to the Action For Community Ltd charity, enabling us to proudly support the local community. Situated in a former textile mill, sporting a distinctive clock tower, Carlisle Business Centre is a landmark of Manningham. The building was extended and revived in 1991 to provide a... Read more

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Random Forest Course Events - Bradford

Random Forest Course Outlines in Bradford

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