boilerplate-machine-learning-dockerfiles-for-miniconda

Boilerplate of Dockerfiles for Jupyter Notebook, Tensorflow, Keras and so on with Miniconda.

Required

• Docker installed

Getting started

• Clone this repo
• Select Dockerfile and Edit dockerfile value in docker-compose.yml
• Run docker-compose up --build in terminal

Default Settings

• Port: 8888:8888
• Volume: ./data:/data
• --notebook-dir: /data/notebooks

Dockerfile List

Dockerfile Name	Main Packages	Virtual Env.	Base Image
Dockerfile.mini.base	Miniconda, Jupyter Notebook	Not used	continuumio/miniconda3
Dockerfile.mini.tensorflow	Miniconda, Jupyter Notebook, Tensorflow	Not used	keidrun/ml-base-mini
Dockerfile.mini.keras	Miniconda, Jupyter Notebook, Tensorflow, Keras	Not used	keidrun/ml-base-mini
Dockerfile.mini.pytorch	Miniconda, Jupyter Notebook, Pytorch	Not used	keidrun/ml-base-mini

Docker Image List

Docker Image Name	Built Dockerfile Name
keidrun/ml-base-mini	Dockerfile.mini.base
keidrun/ml-tensorflow-mini	Dockerfile.mini.tensorflow
keidrun/ml-keras-mini	Dockerfile.mini.keras
keidrun/ml-pytorch-mini	Dockerfile.mini.pytorch

For example, if you'd like to use keidrun/ml-keras-mini image, run the following command:

docker container run -it -p 8888:8888 -v $(pwd)/data:/data keidrun/ml-keras-mini

Or edit image value in docker-compose.image.yml and run the following command:

docker-compose -f docker-compose.image.yml up