Introduction to Clustering - ML with Python - Part - 27
In this video, I will be giving Introduction to Clustering with K-Means where I will talk about what is what clustering is, how it works, why it is used, types of clusters, what is K-Means, etc.
And in this video, I will be implementing this with Python.
What is Clustering in Machine Learning?
Clustering is the task of dividing the population or data points into a number of groups such that data points in the same groups are more similar to other data points in the same group and dissimilar to the data points in other groups.
It is basically a collection of objects on the basis of similarity and dissimilarity between them.
Why is Clustering used in Machine Learning?
The goal of clustering is to find distinct groups or “clusters” within a data set. Using a machine language algorithm, the tool creates groups where items in a similar group will, in general, have similar characteristics to each other.
There are 3 types of learning in Machine Learning.
1. Supervised learning
2. Unsupervised learning
3. Reinforcement learning
My Machine Learning with Python Code Link: https://github.com/9syed/Machine-Lear...