Supervised Learning: Algorithms and Business Use Cases II
Learn to apply supervised learning algorithms like decision trees and random forests to solve real-world business problems. Understand how these models work and discover their applications in medicine, finance, e-commerce, and manufacturing for improved decision making.
We'll cover the following...
We'll cover the following...
Decision trees
These are highly interpretable models that can be used for both classification and regression tasks. They split data-feature values into branches at decision nodes (e.g, if a feature is a color, each possible color becomes a new branch) until a final decision output is made. Decision trees are often fast and accurate and, hence, are widely used.
Image Credits: https://www.cs.bham.ac.uk/~mmk/Teaching/AI
Business use cases
- Understanding product attributes that make a product most likely to be purchased