# Clustering Fundamentals K-Means Unsupervised Learning

The ** k-means clustering** method is an

**unsupervised machine learning**technique used to identify clusters of data objects in a dataset.

*k*-means is one of the oldest and most approachable.

The objective of K-means is to group similar data points together. To achieve this objective, K-means looks for a fixed number (*k*) of clusters in a dataset.

If you’re interested in learning how and when to implement *k*-means clustering in Python, then this is the right place. You’ll walk through an end-to-end example of *k*-means clustering using Python, from preprocessing the data to evaluating results.

**# Maths behind KMeans Algorithm**