k means clustering python github
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Title: A Step-by-Step Guide to K-Means Clustering in Python with GitHub Integration
K-Means clustering is a popular unsupervised machine learning algorithm used for partitioning a dataset into K clusters. In this tutorial, we will walk through the process of implementing K-Means clustering in Python and showcase how to manage the code using GitHub for version control.
Ensure you have the necessary libraries installed by running the following command in your terminal or command prompt:
For this example, let's use a sample dataset. You can replace this with your own dataset.
Ensure the data is in the right format. If necessary, handle missing values or scale the features.
Use the Elbow Method to find the optimal number of clusters.
Now, your K-Means clustering project is on GitHub!
Feel free to modify the code according to your specific use case, and enjoy using K-Means clustering in Python with GitHub integration!
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