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			Reinforcement Learning Explained: Agents, Actions, Rewards & Real-World Applications
								1 year ago							
						
														1						
								
								
												Entertainment					
								
												Do It Yourself					
								
												Reinforcement Learning					
								
												Artificial Intelligence					
								
												Q-learning					
								
												Policy gradients					
								
												Machine learning					
								
												Agents and rewards					
								
												Robotics AI					
								
												Self-driving cars AI					
								
												DeepMind AlphaGo					
					
					
			
	
					In this video, we dive into the fascinating world of Reinforcement Learning (RL) – a key area in Artificial Intelligence (AI). We'll explain the core concepts like agents, actions, and rewards, and how these elements come together to help machines learn from their environments. Explore popular RL algorithms like Q-learning and policy gradients, and see how they're applied in real-world scenarios such as gaming, robotics, and self-driving cars. By the end, you'll have a solid understanding of how RL is transforming industries. Don't forget to like, comment, and subscribe for more AI and tech content!
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