IN-PERSON (Library North Building, Second Floor, Library Classroom 2 computer lab)

GSU Data Ready! Badges Micro-Credentialing: https://lib.gsu.edu/data-ready

This workshop introduces participants to Bagging and Boosting Algorithms using Python.

WORKSHOP TOPICS:

-- Bagging, also known as Bootstrap aggregating, is an ensemble learning technique that helps to improve the performance and accuracy of machine learning algorithms. It is used to deal with bias-variance trade-offs and reduces the variance of a prediction model. Bagging avoids overfitting of data and is used for both regression and classification models, specifically for decision tree algorithms.

-- Boosting algorithms combine multiple weak learners in a sequential method, which iteratively improves observations. This approach helps to reduce high bias that is common in machine learning models.

Prerequisites: 

-- Python for Machine Learning (ML) 4: Decision Trees - live workshop calendar posting: https://rooms.library.gsu.edu/event/11683477

NOTE: Please read our Workshops ~ Etiquette & Policies page for pertinent information to your workshop attendance.

Presenter(s): Ufuk Seçilmiş, M.S. Candidate in the Mathematics & Statistics Department and Graduate Research Assistant with the Library's Research Data Services Team

Checkout our GSU Data Ready! Badges micro-credential courses!

Build your data skills in our workshops and receive digital micro-credential badges to show off your achievements to others.

Learn more about our micro-credential courses at https://lib.gsu.edu/data-ready