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🚗 Self-Driving Car DQN

Welcome to the Self-Driving Car DeepQ Learning Neural Network project! 🤖🚗 This repository houses an exciting Python-based implementation of a self-driving car simulation leveraging the power of Deep Q Learning (DQN) neural networks. Imagine a virtual world where our intelligent car not only roams autonomously but learns from its experiences to become an adept driver!

🌐 Simulation Environment

The heart of this project lies in the simulated environment where our self-driving car learns to navigate and make decisions. This environment is crafted using Python and incorporates the principles of Deep Q Learning to enable the car to respond intelligently to its surroundings. The car's decisions are shaped by its training, creating an adaptive and learning-driven driving experience.

🤖 How It Works

The magic happens through the implementation of a Deep Q Learning neural network. This sophisticated network processes information from the simulated environment, allowing the car to make decisions in real-time. As the car interacts with the environment, the neural network learns and refines its decision-making capabilities, paving the way for a smarter and more capable self-driving car.