Jetware - module: Gflags

tensorflow:1.8.0, keras:2.1.2, python:3.6.3, jupyter_notebook:1.0.0, cuda:9.0.176, cudnn:7.0.5, cuda_only-nvidia_drivers:396.24, opencv:3.4.1, development_preset:1

ricardocerq / dl

tensorflow:1.8.0, keras:2.1.2, python:3.6.3, jupyter_notebook:1.0.0, cuda:9.1.85.3, cudnn:7.1.3, cuda_only-nvidia_drivers:396.24, opencv:3.4.1, development_preset:1

aise / Machine Learning / Education / MIT 6.S094 course: Deep Learning for Self-Driving Cars 2017 / NVidia GPU

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

aise / Machine Learning / Education / MIT 6.S094 course: Deep Learning for Self-Driving Cars 2017 / CPU only

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

aise / Fast.ai Practical Deep Learning for Coders 2018 part 1 NVidia GPU

The pre-configured and ready-to-use runtime environment for the Fast.ai's courses Practical Deep Learning for Coders, 2018 edition, part 1. It includes Python 3.6 and PyTorch 0.3.0. The stack also includes CUDA and cuDNN, and is optimized for running on NVidia GPU.

fast_ai-course:2018-1, cuda:9.0.176, cudnn:7.0.5, cuda_only-nvidia_drivers:384.111