This book provides an introduction to the most important machine learning techniques that are used in predictive data analytics. It discusses both the theoretical concepts that underpin these methods and the practical implementations of these approaches. One of the most prominent uses of machine learning is the construction of prediction models, and another one of its most important application areas is the extraction of patterns from vast datasets. These models are used in several different applications in the academic field of predictive data analytics. Some of these applications include risk assessment, price prediction, forecasting consumer behaviour, and document categorization. Machine learning refers to the method wherein big datasets are automatically analyzed for meaningful patterns.