Perform k$-$means clustering on the same data. Note that you are not supposed to use labels in this case. To measure the "goodness" of clustering, use "Silhouette Score", which Measures how well$-$separated clusters are and how similar data points within the same cluster are. Silhouette Score ranges from $-1$ to $1,$ where a higher score indicates better$-$defined clusters. Try different values of k and show how clustering results changes. Note that you are NOT supposed to use external library for the kmeans clustering algorithm. Using any external library would result in $0$ score.