Brief Tutorial On Unsupervised Learning

Here’s a brief tutorial for unsupervised learning using Python and scikit-learn library:

First, we need to import the necessary libraries and load the dataset:

Next, we need to prepare the data for clustering. This involves removing any unnecessary columns and scaling the data so that all features are on the same scale:

Once the data is prepared, we can apply the KMeans clustering algorithm to the data. In this example, we will use KMeans to cluster the data into three groups:

Finally, we can visualize the clusters using a scatter plot. In this example, we will plot the first two principal components of the data:

Here’s the complete code:

This script demonstrates a simple example of unsupervised learning using KMeans clustering to group data into three clusters, and visualizing the clusters using a scatter plot. Of course, the exact techniques and methods used for unsupervised learning will depend on the specific dataset and problem at hand.

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