This is runtime environment for tutorials of the MIT 6.S094 course: Deep Learning for Self-Driving Cars.
Runtime environment
The runtime environment includes everything needed for the DeepCars and DeepTesla examples and tutorials from the course. All programs are built, installed, configured, tested, and are ready to use.
There are different software bundles (appliances), optimized for different hardware capabilities: x86 CPU only, or x86 CPU with NVidia GPU.
DeepCars
DeepCars include notebooks with an example of implementing the Perceptron, an example of implementing a neural network using TensorFlow. It also includes an example of the traffic light recognition with program code and images for training.
DeepTesla
DeepTesla is a tutorial with the end-to-end steering model using a videostream for input.
The tutorial includes Python script for training and prediction, video files for neural network training (~200 Mb). The neural network and video processing are based on TensorFlow and OpenCV libraries.
The runtime environment constructor for the machine learning and deep learning tutorials and courses.
