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Supervised Machine Learning with Tree Based Models
4.56
Beginner level
3.0 learning hrs
Instructor:
Mr. Bharani Akella
Modules updated 07/2025
About this course
We understand Machine Learning, a subset of Artificial Intelligence, as a computer being programmed with the ability to self-learn and improve itself on a particular task. Supervised Learning in Machine Learning allows one to produce or collect data based on previous experience. It helps one to optimize performance criteria using past experience and work on real-time computational problems. As making Decisions and finding insights from raw data is an essential part of Machine Learning, Tree-based classifiers are widely used for this purpose. Understanding the importance of tree-based classifiers, we have curated this course on tree-based classifiers, which will help you understand various types of supervised learning techniques, such as decision trees, random forests, and how to implement them in Python. The skills covered in this course are NumPy, Pandas, and Scikit Learn Library.
Great Learning has collaborated with the best universities, such as the University of Texas at Austin and SRM Institute of Science and Technology, and created the top AI Courses in India. World-class professors have prepared a comprehensive and exhaustive curriculum to provide learners with a world-class education to develop advanced skills in the online AIML course. The learners will also receive personalized mentorship from industry experts who are working at top organizations.
Check out our PG Course in Machine learning Today.
Course outline
Introduction to Decision Tree
Demo for Decision Tree
Introduction to Random Forest
Demo for Random Forest
Get access to the complete curriculum once you enroll in the course
4.56
Our course instructor
Mr. Bharani Akella
Data Scientist
Machine Learning Expert
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