Cluster Analysis and Unsupervised Machine Learning in Python

Overview

Data science techniques for pattern recognition, data mining, k-means clustering, and hierarchical clustering, and KDE. What you'll learn: Understand the regular K-Means algorithmUnderstand and enumerate the disadvantages of K-Means ClusteringUnderstand the soft or fuzzy K-Means Clustering algorithmImplement Soft K-Means Clustering in CodeUnderstand Hierarchical ClusteringExplain algorithmically how Hierarchical Agglomerative Clustering worksApply Scipy's Hierarchical Clustering library to dataUnderstand how to read a dendrogramUnderstand the different distance metrics used in clusteringUnderstand the difference between single linkage, complete linkage, Ward linkage, and UPGMAUnderstand...