Boilerplate of Dockerfiles for Jupyter Notebook, Tensorflow, Keras and so on with Anaconda.
- Docker installed
- Clone this repo
- Select
Dockerfileand Editdockerfilevalue indocker-compose.yml - Run
docker-compose up --buildin terminal
- Port:
8888:8888 - Volume:
./data:/data - --notebook-dir:
/data/notebooks
| Dockerfile Name | Main Packages | Virtual Env. | Base Image |
|---|---|---|---|
| Dockerfile.tensorflow-env | Anaconda, Jupyter Notebook, Tensorflow | Activated | continuumio/anaconda3 |
| Dockerfile.ana.base | Anaconda, Jupyter Notebook | Not used | continuumio/anaconda3 |
| Dockerfile.ana.tensorflow | Anaconda, Jupyter Notebook, Tensorflow | Not used | keidrun/ml-base |
| Dockerfile.ana.keras | Anaconda, Jupyter Notebook, Tensorflow, Keras | Not used | keidrun/ml-base |
| Dockerfile.ana.pytorch | Anaconda, Jupyter Notebook, Pytorch | Not used | keidrun/ml-base |
| Docker Image Name | Built Dockerfile Name |
|---|---|
| keidrun/ml-base | Dockerfile.ana.base |
| keidrun/ml-tensorflow | Dockerfile.ana.tensorflow |
| keidrun/ml-keras | Dockerfile.ana.keras (outdated) |
| keidrun/ml-pytorch | Dockerfile.ana.pytorch |
NOTE: Tensorflow 2.0 supports Keras so use an above tensorflow image if you'd like a keras image.
For example, if you'd like to use keidrun/ml-keras image, run the following command:
docker container run -it -p 8888:8888 -v $(pwd)/data:/data keidrun/ml-kerasOr edit image value in docker-compose.image.yml and run the following command:
docker-compose -f docker-compose.image.yml up
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