Summary

The final class of the AI course reviews key concepts and applications of AI, focusing on machine learning and natural language processing. It covers the types of machine learning, including supervised, unsupervised, and reinforcement learning, with a focus on supervised learning's classification and regression. The importance of data and datasets is highlighted, and the class concludes with an examination of decision trees and pruning techniques.

What are the two main types of artificial intelligence discussed in the course?

• Machine learning and deep learning

• Machine learning and natural language processing

• Deep learning and robotics

• Natural language processing and robotics

Which type of machine learning focuses on predicting data categories?

• Regression

• Classification

• Unsupervised learning

• Reinforcement learning

What is the role of datasets in machine learning?

• They are used to train models

• They are used to test models

• They are used to validate models

• They are used to improve model accuracy

What is a decision tree?

• A neural network model

• A clustering algorithm

• A tree-like structure for decision making

• A linear model for regression

How can the performance of a decision tree be improved?

• By increasing the number of nodes

• By using a different algorithm

• By using a technique called pruning

• By adding more branches