Develop an AI system to solve a real-world problem : Classification versus Regression

The video tutorial introduces supervised learning, focusing on classification and regression. It explains the general pipeline of supervised learning, including data collection, training, and testing. The tutorial discusses various techniques, such as support vector machines (SVMs) for classification and artificial neural networks for regression. A practical example using SVM is demonstrated, highlighting the process of training a model and making predictions.

In what ways can regression algorithms be applied to business problems?

What is the significance of training and testing data in supervised learning?

Discuss the importance of having sufficient data for training supervised learning models.

How can classification problems be treated as a special case of regression problems?