Module
stanford-cs231n-course
Branches
Role
Description
This is a software bundle for the CS231n Spring 2017 course from Stanford University - Convolutional Neural Networks for Visual Recognition.
Runtime environment
This runtime environment includes everything needed for the tutorials and assignments used in this course. All the software components are built, installed, configured, and tested, and are ready to use.
Web site
The runtime environment constructor for the machine learning and deep learning tutorials and courses.
The pre-configured and ready-to-use runtime environment for the CS231n course - Convolutional Neural Networks for Visual Recognition, Stanford University, Spring 2017. It includes latest versions of Python 3, TensorFlow, and PyTorch. The stack also includes CUDA and cuDNN, and is optimized for running on NVidia GPU.
stanford-cs231n-course:1617spring, tensorflow:1.5.0, pytorch:0.3.0, keras:2.1.2, python:3.6.3, cuda:9.0.176, cudnn:7.0.5, cuda_only-nvidia_drivers:384.111
The pre-configured and ready-to-use runtime environment for the CS231n course - Convolutional Neural Networks for Visual Recognition, Stanford University, Spring 2017. It includes latest versions of Python 3, TensorFlow, and PyTorch. The software stack is optimized for running on CPU.
stanford-cs231n-course:1617spring, tensorflow:1.5.0, pytorch:0.3.0, keras:2.1.2, python:3.6.3
The pre-configured and ready-to-use runtime environment for the CS231n course - Convolutional Neural Networks for Visual Recognition, Stanford University, Spring 2017. It includes latest versions of Python 2, TensorFlow, and PyTorch. The stack also includes CUDA and cuDNN, and is optimized for running on NVidia GPU.
stanford-cs231n-course:1617spring, tensorflow:1.5.0, pytorch:0.3.0, keras:2.1.2, python:2.7.14, cuda:9.0.176, cudnn:7.0.5, cuda_only-nvidia_drivers:384.111
The pre-configured and ready-to-use runtime environment for the CS231n course - Convolutional Neural Networks for Visual Recognition, Stanford University, Spring 2017. It includes latest versions of Python 2, TensorFlow, and PyTorch. The software stack is optimized for running on CPU.
stanford-cs231n-course:1617spring, tensorflow:1.5.0, pytorch:0.3.0, keras:2.1.2, python:2.7.14
The pre-configured and ready-to-use runtime environment for the CS231n course - Convolutional Neural Networks for Visual Recognition, Stanford University, Spring 2017. It includes original (old) versions of Python, TensorFlow, and PyTorch, used in the course. The stack also includes CUDA and cuDNN, and is optimized for running on NVidia GPU.
stanford-cs231n-course:1617spring, tensorflow:1.0.1, pytorch:0.1.11, keras:2.0.2, python:3.5.4, cuda:8.0.61, cudnn:5.1.10, cuda_only-nvidia_drivers:384.111
