Clustering is like sorting or grouping similar things together. Clustering in the context of computers and data means using special techniques to do this automatically, without having to decide in advance how many piles or groups there should be.

It’s a way to find patterns or groups in data, which can be helpful for many things like organizing information, understanding customer behavior, or even organizing photos on your computer.

K-means Clustering:

• K-means is like sorting things into groups based on their similarity.
• We can decide how many groups we want, and the computer puts things in those groups.
• It keeps moving things around until it finds the best groups.

Hierarchical Clustering:

• Hierarchical clustering is like building a family tree for data.
• It starts with every item in its own family, and then it joins them together step by step, like merging families in a family tree.
• This is how things are related at different levels, from big groups to smaller ones.