What is the difference between Reinforcement Learning and Deep Reinforcement Learning ?

Reinforcement Learning (RL) involves training models to make decisions through trial and error, learning from interactions with an environment. On the other hand, Deep Reinforcement Learning (DRL) combines RL with deep neural networks, enabling the system to handle more complex tasks by automatically extracting features from raw data. In essence, Deep Reinforcement Learning extends traditional Reinforcement Learning by leveraging the power of deep learning techniques, allowing for more sophisticated and nuanced decision-making processes.