This chapter covers the less commonly used topics, such as machine learning with multiple classes and GPU-based optimizations. Both the topics are seeing a growth in interest and practical applications, so they deserve a complete chapter. We consider them advanced only as long as additional knowledge is required about machine learning / statistical classification and parallelization. We will start by explaining some of the most well-known classifiers such as KNN, SVM, and Random Forests, all of which are available in the ml module and show how they work with different database formats and multiple classes. Finally, a set of classes and functions to utilize GPU-based computational resources will be described.