In this project, I Implemented K-Means clustering on the well-known Iris dataset to classify iris flowers into distinct groups based on their sepal and petal measurements. ✔️I utilized the Elbow Method to determine the optimal number of clusters, enhancing model performance. ✔️To visualize the clusters effectively, I employed Principal Component Analysis (PCA) to reduce the dataset to two dimensions. This approach provided clear visual separation of the clusters and highlighted the centroids.