Workshop 08 | Machine Learning: Zero to Hero
The decision tree builds regression or classification models in the form of a tree structure. It breaks down a dataset into smaller and smaller subsets while at the same time an associated decision tree is incrementally developed. The final result is a tree with decision nodes and leaf nodes.
Random Forest Regression is a supervised learning algorithm that uses ensemble learning methods for regression. The ensemble learning method is a technique that combines predictions from multiple machine learning algorithms to make a more accurate prediction than a single model.
In this detailed workshop, we will understand the core concepts of Tree-based ML Models and will implement both techniques, Decision Tree & Random Forest Regression.
Lenaar Digital
Co-founder
AI Engineer at ReliefMe.org
Lead at Developer Student Clubs
Microsoft Student Ambassador
GDSC Lead
SPARK⚡BIZ
Community Mentor
Techrics
Outreach Coordinator
Media Creative Lead
Tech Lead
AI and Chatbot Developer | Full Stack Web | PAFLA Ambassador | Public Speaker | Trainer
Communications Lead
Softseek International
Operations Lead
Marketing Lead
Sir Syed University of Engineering & Technology
Event Management Lead
Content Writing Lead
HnH Soft Tech Solutions Pvt Ltd
Host
