Machine Learning with Python: k-Means Clustering
K-means clustering is one of the most popular and easy to use clustering algorithms. In this course, Fred Nwanganga gives an introductory look at k-means clustering—how it works, what it’s good for, when you should use it, how to choose the right number of clusters, its strengths and weaknesses, and more. I learned how K-means clustering is used in market segmentation, medical imaging, and anomaly detection. Through hands on guidance, I was able to learn how to collect, explore, and transform data in preparation for segmenting data using K-means clustering while also being able to build such a model in python.