Tutorials, assignments, and competitions for MIT Deep Learning related courses.
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This repository is a collection of tutorials for MIT Deep Learning courses. More added as courses progress.
This tutorial accompanies the lecture on Deep Learning Basics. It presents several concepts in deep learning, demonstrating the first two (feed forward and convolutional neural networks) and providing pointers to tutorials on the others. This is a good place to start.
This tutorial demostrates semantic segmentation with a state-of-the-art model (DeepLab) on a sample video from the MIT Driving Scene Segmentation Dataset.
This tutorial explores generative adversarial networks (GANs) starting with BigGAN, the state-of-the-art conditional GAN.
DeepTraffic is a deep reinforcement learning competition. The goal is to create a neural network that drives a vehicle (or multiple vehicles) as fast as possible through dense highway traffic.