The aim is to get familiar with the fundamental theoretical concepts in machine learning, as well as practical aspects of applying machine learning algorithms using machine learning life Cycle.
Key techniques are demonstrated in supervised machine learning, such as classification using decision trees and nearest neighbor algorithms, and regression analysis. There is a special focus on evaluating the efficiency of these algorithms. A series of common clustering algorithms are shown in detail in unsupervised machine learning.