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.