This course covers the concept of clustering in machine learning. It explains three of the most common clustering algorithms, with a hands-on approximation to solve a real-life data problem. The three clustering algorithms covered are k-means, mean-shift and DBSCAN algorithms. This course is part of The Machine Learning learning path– complete this path to build and deploy Machine learning models using Python libraries.
Knowledge and experience in Python programming are a must. No prior knowledge of scikit-learn or machine learning algorithms is required.