Resources

The following tutorials, videos, blogs, and papers are excellent resources for additional study before, during, and after the class.  Note: 6.S094 is designed for people who are new to programming, machine learning, and robotics. The following are optional resources for longer-term study of the subject.

Course Tutorials

The following tutorials help introduce Python, TensorFlow, and the two autonomous driving simulations described in the class.

Getting Started

Deep Learning Details

  • Deep Learning Book – An excellent comprehensive textbook on deep learning. Up to this point, the review of deep learning fundamentals have been spread across multiple books, papers, and blogs. Now it’s all together in one place.
  • CS231n Convolutional Neural Networks for Visual Recognition – While this Stanford class is presumably focused on computer vision, it happens to have the hands down best introduction to deep learning I’ve seen anywhere both in its notes and its video lectures.
  • Andrej Karpathy blog – One of the instructors of CS231n keeps a great blog with should be required reading for all interested in machine learning because its very digestable, entertaining, and doesn’t hold back on the messy details.

Deep Reinforcement Learning

Recurrent Neural Networks

Autonomous Vehicles and ADAS