Let's check the efficiency of the algorithm on different types of clusters. Now we will use the three built-in datasets of the sklearn library and try to use the K-means algorithm to cluster the corresponding points. We will provide visualizations and try to estimate the quality of clustering using these visualizations.

Your task is to use the K-means clustering algorithm and to solve 3 different clustering problems. Compare the results and make conclusions about clustering quality. You have to:

1. Use KMeans class from cluster module for import.
2. Use KMeans class to instantiate a class object
3. Use.fit()method to train model.
4. Use .labels_attribute to extract fitted clusters.

_{Once you've completed this task, click the Submit Task button below the code to check your solution.}