Machine Learning (ML) and Deep Learning (DL) comprise a broad and powerful set of tools, techniques, and algorithms that underly the functioning of many AI systems, and are important components in a number of data processing and modeling pipelines. While we are emphasizing here a conceptual separation of AI functionality from ML and DL implementations, much of the ongoing discussion about AI blurs these boundaries, so it is worthwhile to discuss some of those implementation details in the context of the larger field of functionality and applications. Our intent in this topic is to provide a higher-level conceptual overview of ML and DL to provide some context and background for understanding the capabilities of AI systems. For more detailed information about specific types of algorithms and software tools for carrying out ML and DL computations, readers are encouraged to consult our companion materials on AI with Deep Learning and Python for Data Science.