EMLI (Exxact Machine Learning Images): Pre-installed Developer-Ready Environment
We understand every development environment is different, so shouldn't you have the option to choose what's best for you? All EMLI environments are available in the latest Ubuntu or CentOS Linux versions, and are built to perform right out of the box.
Find Your Perfect Deep Learning Environment with EMLI
| Most Popular | |||
Compare*Additional NGC (NVIDIA GPU Cloud) containers can be added upon request. |  Conda EMLISeparated Frameworks |  Container EMLIFlexible. Reconfigurable. |  DIY EMLISimple. Clean. Custom. |
|---|---|---|---|
Who is it for? | For developers who want pre-installed deep learning frameworks and their dependencies in separate Python environments installed natively on the system. | For developers who want pre-installed frameworks utilizing the latest NGC containers, GPU drivers, and libraries in ready to deploy DL environments with the flexibility of containerization. | For experienced developers who want a minimalist install to set up their own private deep learning repositories or custom builds of deep learning frameworks. |
Frameworks* | |||
| TensorFlow V1 | — | — | |
| TensorFlow V2 | — | ||
| PyTorch | — | ||
| MXnet | — | ||
| Caffe | — | — | |
| Caffe2 | — | ||
| Chainer | — | — | |
| Microsoft Cognitive Toolkit | — | — | |
Libraries* | |||
| NVIDIA cuDNN | |||
| NVIDIA Rapids | — | — | |
| Keras | — | ||
| Theano | — | ||
| OpenCV | — | ||
Software Environments | |||
| NVIDIA CUDA Toolkit | |||
| NVIDIA CUDA Dev Toolkit | — | ||
| NVIDIA Digits | — | — | |
| Anaconda | — | ||
Container Management | |||
| Docker | — | ||
Drivers | |||
| NVIDIA-qualified Driver | |||
Orchestration | |||
| Micro-K8s | Free upgrade available | Free upgrade available | Free upgrade available |