Data Science Talks Machine-Learning and Artificial Intelligence

We start out by covering the topic of clustering. Clustering is essentially grouping pieces of information by similarity. For instance, imagine a large set of images that you want to group based on their similarities; clustering would be our primary choice for such a process. The chapter also covers high dimensionality and features, which are essential for understanding later chapters. We also cover kmeans and DBSCAN clustering algorithms in some depth to help show the reader how they work under the hood.