Docker for Data Science | Deep Learning

Ready-to-run Docker image containing Jupyter applications and interactive computing tools for Data Science and Deep Learning.

Specs

The image is built on top of python 3.6 (docker image) and has these packages built into it. It comes with the following installed packages:

• Python Version: 3.6
• Tensorflow - 1.7
• Tensorflow Object detection and its dependencies
• Keras (latest)
• Numpy 1.13.3
• Scipy (latest)
• Sklearn (latest)
• Open CV (latest)
• Scikit Image (latest)
• Matplotlib (latest)
• Seaborn (latest)
• Jupyter Notebook (latest)
• Pillow (latest)

The following ports have been exposed:

• 8888 for Jupyter Notebook
• 6006 for Tensor Board

It also comes with a collection of extensions that add functionality to the Jupyter notebook. For more information see here.

Setup

1. Install Docker CE (Install)

2. Pull the image docker pull achilleaskn/docker_data_science

3. Run the image (interactive mode) docker run -i -t -p 8888:8888 achilleaskn/docker_data_science /bin/bash

4. Start Jupyter Notebook jupyter notebook --port=8888 --no-browser --ip='0.0.0.0' --allow-root

5. Open your browser and go to localhost:8888 and use the password thisismypassword to login into the jupyter notebook