Machine Learning Random Forest with Python from Scratch - Clustering

The video tutorial introduces clustering, a branch of unsupervised learning in machine learning, which involves grouping similar features without labels. It emphasizes the importance of understanding the difference between regression and classification. The tutorial explains how clustering works by grouping data points based on similarities and discusses various clustering algorithms like K-means, fuzzy C-means, EM, and hierarchical clustering. The video concludes with a preview of the next lecture on the general flow of a machine learning project.

How would you determine which cluster a new data point belongs to?

What are some examples of clustering algorithms mentioned in the text?