Data Science and Machine Learning (Theory and Projects) A to Z - Machine Learning Methods: Clustering

The video tutorial introduces clustering, a type of unsupervised learning where data is grouped based on similarity without predefined labels. It explains the process of clustering, differentiates it from classification, and describes how to generate group labels for data points. The tutorial concludes with a mention of a practical example using Jupyter Notebook and Scikit-learn in the next video.

What is clustering and how does it relate to unsupervised learning?

How do you determine the similarity between different objects in clustering?

Explain the difference between clustering and classification.

Why is it important to generate labels in clustering, and how are they created?

What steps would you take to group data points into clusters?