Machine Learning: Random Forest with Python from Scratch - Classification versus Regression

The video tutorial covers the types of machine learning, focusing on supervised learning's classification and regression. Classification deals with categorical outputs, such as spam detection, while regression involves continuous outputs, like predicting salaries. Various algorithms for both methods are discussed, including logistic regression and random forest. The tutorial concludes with a preview of clustering, an unsupervised learning technique.

What is the significance of labeled data in supervised machine learning?

How can the random forest algorithm be utilized in both classification and regression?

What is clustering and how does it differ from supervised learning methods?