Tag: Deep Reinforcement Learning

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Deep learning – Introduction to Powerful Deep Reinforcement Learning

Through the use of deep neural networks, the agent can learn directly from raw data, enabling it to handle high-dimensional input spaces and complex decision-making processes. Deep Reinforcement Learning finds practical applications in robotics, gaming, natural language processing, and other fields where autonomous decision-making is crucial.

Deep Learning – Mandate for Humans, Not Just Machines

Deep Learning terminology can be quite overwhelming to newcomers.. This blog post covers important aspect of deep learning which can be defined as set of techniques that uses neural networks to simulate human decision-making skills. #AILabPage

Reinforcement Learning

Reinforcement Learning – Reward for Learning

Reinforcement learning can be understood by using the concepts of agents, environments, states, actions and rewards. This is an area of machine learning; where there’s no answer key, but RL agent still has to decide how to act to perform its task. The agent is inspired by behaviourist psychology who decide how and what actions will taken in an environment to maximize some notion of cumulative reward.