Clustering Algorithms Made Easy: Hierarchical agglomerative clustering K-means DBSCAN Neural network-based clustering You will learn different strengths and weaknesses of these algorithms as well as the practical strategies to overcome the weaknesses. In addition, we will briefly touch upon some other clustering methods. The examples of the algorithms are presented in Python 3. We will work with several datasets, including the ones based on real-world data. We will be primarily working with the Scikit-learn and SciPy libraries. But our neural network for clustering, we will build basically from scratch, just by using NumPy arrays.
Author: Artem Kovera