K-Means Clustering Tutorial in Python - [Mubaris NK]

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Mubaris NK, an IT student at IIITA, has created a tutorial on K-Means Clustering in Python and posted it on his website.

Some of you who are familiar with machine learning might know that K-Means Clustering is an algorithm often implemented in unsupervised learning to find patterns/meaning in unlabeled data - that is to find clusters.

In his tutorial, Mubaris implements a K-Means algorithm from scratch in Python. He starts with a graphical representation of the algorithm on a hypothetical dataset.

He then provides some uses for K-Means and goes into the mathematics of it, which I think is important to understand if you want to get a good hold on how it all works.

Then, he follows with an implementation in Python, using NumPy, Pandas, and Matplotlib (for visualization).

Mubaris also shows us how to implement K-Means in scikit-learn, a library that I've created many ML tutorials on.

I like to read, follow, go through tutorials that include a lot graphical representations of the concepts that are illustrated. I think this aids the process of learning. Mubaris NK's tutorials is in this category. So, if you want to learn more about K-Means and unsupervised learning, I'd recommend looking through it, and of course, coding along:

K-Means Clustering Tutorial in Python - [Mubaris NK]

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Cristi Vlad Self-Experimenter and Author