Appliances
![Tensorflow15_keras21_python27_cuda9_notebook default](/ic/appliances/max/_default.png)
A pre-configured and fully integrated minimal runtime environment with TensorFlow, an open source software library for machine learning, Keras, an open source neural network library, Jupyter Notebook, a browser-based interactive notebook for programming, mathematics, and data science, and the Python programming language. The stack is optimized for running on NVidia GPU.
![Tensorflow-1 Tensorflow](/ic/packages/min/tensorflow.png)
![Keras-2 Keras](/ic/packages/min/keras.png)
![Python-2 Python](/ic/packages/min/python.png)
![Jupyter_notebook-1 Jupyter notebook](/ic/packages/min/jupyter_notebook.png)
![Cuda-9 Cuda](/ic/packages/min/cuda.png)
![Cudnn-7 Cudnn](/ic/packages/min/cudnn.png)
![Cuda_only-nvidia_drivers-384 Nvidia drivers](/ic/packages/min/nvidia_drivers.png)
![Development_preset-1 Preset](/ic/packages/min/preset.png)
![Tensorflow15_python2_cuda9 Machine learning](/ic/appliances/max/machine_learning.png)
A pre-configured and fully integrated software stack with TensorFlow, an open source software library for machine learning, and Python 2.7. It provides a stable and tested execution environment for training, inference, or running as an API service. The stack can be easily integrated into continuous integration and deployment workflows. It is designed for short and long-running high-performance tasks and optimized for running on NVidia GPU.
![Tensorflow-1 Tensorflow](/ic/packages/min/tensorflow.png)
![Python-2 Python](/ic/packages/min/python.png)
![Cuda-9 Cuda](/ic/packages/min/cuda.png)
![Cudnn-7 Cudnn](/ic/packages/min/cudnn.png)
![Cuda_only-nvidia_drivers-384 Nvidia drivers](/ic/packages/min/nvidia_drivers.png)
![Development_preset-1 Preset](/ic/packages/min/preset.png)
![Course_stanford_cs224n_2018_python2_cuda9 Course stanford](/ic/appliances/max/course_stanford.png)
The pre-configured and ready-to-use runtime environment for the Stanford's CS224n course: Natural Language Processing with Deep Learning. It includes Python 2.7 and TensorFlow 1.4.1. The stack also includes CUDA and cuDNN, and is optimized for running on NVidia GPU.
![Stanford-cs224n-course-2018 Course](/ic/packages/min/course.png)
![Python-2 Python](/ic/packages/min/python.png)
![Cuda-9 Cuda](/ic/packages/min/cuda.png)
![Cudnn-7 Cudnn](/ic/packages/min/cudnn.png)
![Cuda_only-nvidia_drivers-384 Nvidia drivers](/ic/packages/min/nvidia_drivers.png)
![Course_stanford_cs231n_1617spring_python2_cuda9_latest Course stanford](/ic/appliances/max/course_stanford.png)
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 Course](/ic/packages/min/course.png)
![Tensorflow-1 Tensorflow](/ic/packages/min/tensorflow.png)
![Pytorch-0 Pytorch](/ic/packages/min/pytorch.png)
![Keras-2 Keras](/ic/packages/min/keras.png)
![Python-2 Python](/ic/packages/min/python.png)
![Cuda-9 Cuda](/ic/packages/min/cuda.png)
![Cudnn-7 Cudnn](/ic/packages/min/cudnn.png)
![Cuda_only-nvidia_drivers-384 Nvidia drivers](/ic/packages/min/nvidia_drivers.png)