End-to-end learning using CARLA Simulator

End-to-end learning refers to using a single system/model to perform complex tasks instead of breaking them into smaller simple tasks. One such complex task is driving. We, humans, are born with state-of-the-art capabilities when it comes to vision and learning complex tasks. Therefore it might seem simple when we look at it as humans, but we only realize the complexity when we have to build a system to carry out the same task. In this blog, we will try to demonstrate how end-to-end learning can be used to solve the driving problem by using convolutional Neural Networks.