This chapter leads us into the field of machine learning. We first retrospect the origins of machine learning, introduce some typical definitions, and demystify the distinction between machine learning and human learning. Next, we survey the related fields such as artificial intelligence, deep learning, statistical learning, pattern recognition, and data mining. We then turn to review the historical trajectory of machine learning, spotlighting the pivotal development paths: neural networks, decision trees, boosting methods, support vector machines, and reinforcement learning. After that, we delve into the practical realm by showcasing representative applications like computer vision, speech recognition, natural language processing, data mining, computer games, autonomous technologies, medicine, biology, and so on. At the end of this chapter, we finally invoke “The Too-Small World” for a succinct discussion on machine learning.