Hand gesture recognition is probably one of the most critical technologies that support human-computer interaction. This capability allows machines to interpret hand gestures and increase the basis of human-computer communication. Beyond such forms of communication, this ability enlarges the scope of interactive systems in fields like game, virtual reality, robotics, and even health care. A complete hand gesture recognition system and its implementation through the use of some components, or modules, are widely described in this paper. We discuss the underlying technologies, feature extraction methods, classification algorithms, and real-world applications, finding major challenges and future research directions. New contribution for this paper is on hybrid models of deep learning and classical methods demonstrating superior performance within a real-time environment. These findings are crucial to devise more efficient, accurate, and user-friendly HCI systems. Hand gesture recognition is probably one of the most critical technologies that support human-computer interaction. This capability allows machines to interpret hand gestures and increase the basis of human-computer communication. Beyond such forms of communication, this ability enlarges the scope of interactive systems in fields like game, virtual reality, robotics, and even health care. A complete hand gesture recognition system and its implementation through the use of some components, or modules, are widely described in this paper. We discuss the underlying technologies, feature extraction methods, classification algorithms, and real-world applications, finding major challenges and future research directions. New contribution for this paper is on hybrid models of deep learning and classical methods demonstrating superior performance within a real-time environment. These findings are crucial to devise more efficient, accurate, and user-friendly HCI systems.