UNSUPERVISED LEARNING: Clustering…

1. 1Apply K-Means clustering algorithm to a dataset using scikit-learn library
2. 2Configure the number of clusters (K) using the Elbow method
3. 3Test the clustering model using silhouette score
4. 4Run hierarchical clustering to visualize the dendrogram
5. 5Compare the results of different clustering algorithms to choose the best one

Data scientists and analysts can benefit from unsupervised learning to identify meaningful clusters in their data, while machine learning engineers can use this technique to improve model performance

💡 Unsupervised learning can reveal meaningful clusters in unlabeled data, improving model performance and insight discovery

🤖 Unsupervised learning helps uncover hidden patterns in data! #MachineLearning #UnsupervisedLearning