Artificial Intelligence (AI) is transforming how tasks are performed by machines, particularly through computer systems capable of calculation, learning, and responding to stimuli in ways that mimic human cognitionHuman cognition. A critical subset of AI is Machine Learning (ML), which focuses on the learning process. Much like the human brain, ML systems analyze data inputs, retain relevant information, and produce outputs as numerical or coded representations for decision-making or display purposes. The potential of AI and ML to revolutionize industries has made them central topics of discussion in recent years. This chapter introduces the types of machine learning algorithmsMachine learning algorithms (MLA) that are used throughout this book. It will serve as a reference source as various MLA get referred to in different chapters but the description of how they operate is discussed here. They are four main MLA used: There are other algorithms, lassoLasso, normal ridge regressionNormal ridge regression, decision trees, adaptive boostingAdaptive boosting, k-nearest neighborsK-nearest neighbors, that were evaluated in specific problem areas. They are not discussed in this chapter but introduced instead where they appear in this manuscript. In addition before any algorithm can operate, datasets need preprocessing. This mathematical operation is discussed here. The methods of interpreting results and evaluating their quality are also discussed here.