davidamom/jupyter-keras repository overview

⁠jupyter-keras

⁠Info

Extended from Jupyter Notebook Scientific Python Stack⁠ which contains :

• Jupyter Notebook 5.2.x
• Conda Python 3.x environment
• pandas, matplotlib, scipy, seaborn, scikit-learn, scikit-image, sympy, cython, patsy, statsmodel, cloudpickle, dill, numba, bokeh, vincent, beautifulsoup, xlrd pre-installed

Check Jupyter Github given above for full reference and usage. Everything is pre-installed for Python 3.x.

Image build is triggered with each update of Jupyter Notebook Scientific Python Stack⁠ and install bleeding edge versions of Keras.

For advanced usage and options, read more at Jupyter Notebook Scientific Python Stack⁠.

I use this image to work with neural networks, so I added the following libraries :

• Keras⁠: a high-level neural networks API, written in Python and capable of running on top of TensorFlow, CNTK, or Theano. It was developed with a focus on enabling fast experimentation.
• TensorFlow⁠: open source software library for numerical computation using data flow graphs, the default backend for Keras.
• HDF5 for Python⁠: optional dependency of Keras used to save / load weights for neural networks.

Note : in this setting, TensorFlow will be CPU enabled only.

⁠Basic Use

docker run -d -v /$(pwd)/:/home/jovyan/work \
           -p 8888:8888 davidamom/jupyter-keras start-notebook.sh --NotebookApp.token=''

This will allow to have the current working directory path mounted directly into the guest and with no password