• Overview : This repository contains an AI model that utilizes Deep Q-Learning (DQN) to master the CartPole-v0 environment from OpenAI Gym. The model learns to balance a pole on a moving cart, achieving stability over time.

• Features Deep Q-Learning (DQN): The model employs a DQNAgent, a reinforcement learning technique, to learn optimal actions over episodes.

• CartPole-v0 Environment: The model is trained and evaluated in the CartPole-v0 environment provided by OpenAI Gym.

• TensorFlow Implementation: The DQN agent is implemented using TensorFlow, providing a scalable and efficient deep learning framework.