We bring you a tutorial on Supervised Machine Learning with Tree-Based Models! 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.

Great Learning brings you this tutorial on Supervised Machine Learning with Tree-Based Models where we learn supervised machine learning through tree-based algorithms. This video starts off with the decision tree algorithm, followed by looking at the decision tree algorithm in Python. Then we look at the random forest algorithm and then see how the random forest algorithm works in Python. This video teaches Supervised Machine Learning with Tree-Based Models and its key functions and concepts with a variety of demonstrations & examples.

• 0:00:00 Introduction
• 0:01:36 Agenda
• 0:02:03 Decision Tree Algorithm
• 0:15:36 Decision Tree in Python
• 0:45:40 Random Forest Algorithm
• 0:53:13 Random Forest in Python

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