Reinforcement Q-Learning and Markov Decision Processes Reinforcement Learning Concepts Introduction, Learning tasks Q-Learning and Deep Q-Learning Markov Decision Processes (MDP) Policy Gradient Methods Rewards and Actions, Temporal Difference Learning Generalizing from examples, the Relationship to Dynamic Programming Reinforcement Learning Definition: Reinforcement learning is a type of machine learning where an agent learns through trial and error to achieve a specific goal by maximizing a reward function.
."Discover how machine learning algorithms can be used to predict customer behaviour and improve business outcomes. Learn how to leverage the power of data to drive success." Machine learning is a subfield of artificial intelligence that focuses on the development of algorithms and models. Machine learning has numerous applications in various fields such as computer vision, natural language processing, speech recognition, robotics, finance, healthcare, and more