This chapter explores the integration of machine learning (ML) concepts within the realm of power electronics. It begins by discussing the foundational principles of ML, followed by an overview of its various types. Each type is explained using specific examples relevant to power electronics, illustrating their practical applications. Widely used ML algorithms in power electronics are examined, highlighting their advantages and providing simple explanations of their concepts and mathematical foundations. The general steps involved in the ML process are outlined, with real-time deployment considerations set aside for discussion in subsequent chapters. To enhance the understanding of these steps and the implementation of ML algorithms, a step-by-step guide is included to demonstrate their effectiveness in power electronics. Finally, this chapter presents a list of available resources, including datasets relevant to power electronics, as well as the software tools and programming languages necessary for building ML algorithms. This chapter aims to equip readers with a comprehensive understanding of the fundamentals of ML in the context of power electronics.