achilleaskn/docker_data_science repository overview

⁠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