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Built and trained a convolutional neural network for end-to-end driving in a simulator, using TensorFlow and Keras. Used optimization techniques such as regularization and dropout to generalize the network for driving on multiple tracks.
Keras/Tensorflow Implementation of `End-to-End Learning for self-driving car (Nvidia)`. Spatial factorization is additionally implemented to reduce network size.
Project including multiple machine learning and computer vision tasks to accommodate a digitalized data universe for the designated car and automate different driving processes. 🏎