Version
Course
mit-mit_6_s094-course:2017
Version
2017
Role
Description

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.

Machine learning education

The runtime environment constructor for the machine learning and deep learning tutorials and courses.

Course mit
The pre-configured and ready-to-use runtime environment for the MIT 6.S094 course: Deep Learning for Self-Driving Cars, 2017. It includes Python 2.7, TensorFlow 0.12.1 and OpenCV 3.3.0. The stack also includes CUDA and cuDNN, and is optimized for running on NVidia GPU.
mit-mit_6_s094-course:2017, cuda:8.0.61, cudnn:5.1.10, cuda_only-nvidia_drivers:384.111
Course mit
The pre-configured and ready-to-use runtime environment for the MIT 6.S094 course: Deep Learning for Self-Driving Cars, 2017. It includes Python 2.7, TensorFlow 0.12.1 and OpenCV 3.3.0. The software stack is optimized for running on CPU.
mit-mit_6_s094-course:2017