Zhenye-Na/e2e-learning-self-driving-cars
π ππππππππππ PyTorch implementation of "End-to-End Learning for Self-Driving Cars" (arXiv:1604.07316) with Udacity's Simulator
This project helps develop and test AI models for self-driving cars. It takes recordings of a car driving in a simulation environment, including camera images and steering angles, and trains a neural network to predict the correct steering angle. The output is a trained AI model that can autonomously steer a virtual car. This is useful for researchers and engineers working on autonomous vehicle control systems.
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Use this if you are an autonomous driving researcher or engineer looking to train and evaluate a self-driving car model using simulation data and a PyTorch framework.
Not ideal if you are looking for a plug-and-play solution for real-world autonomous driving or if you are not comfortable with machine learning model training workflows.
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Jupyter Notebook
License
MIT
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Last pushed
May 23, 2022
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