Week 0 - Jupyter notebook with Keras and Tensorflow

Starting with my deep-learning learning plan, I wanted to have a good development environment. This meant having a Docker image that can work on any device I am using with no extra setup needed. My choice was to use Keras with Tensorflow core for an easy start with not so many unwanted details at this step. I also chose to use Jupyter notebook to have a nice interface to trace/explain my code along with graphs and output numbers.

The following is my finalized Dockerfile with the latest versions which worked exactly how I wanted it.

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# To build the container # docker build -t jupyter-keras . # To run the container: # docker run -it -v /$(pwd)/:/home/jovyan/work -p 8888:8888 jupyter-keras:latest start-notebook.sh --NotebookApp.token=''   # To access the notbook from the browser: # http://localhost:8888/tree   # To login in to the server: # docker exec -it <container id=""> /bin/bash   # To check Keras version: # python -c 'import keras; print(keras.__version__)'   FROM jupyter/scipy-notebook   MAINTAINER Gaarv <@Gaarv1911>   USER root   # bash instead of dash to use source RUN ln -snf /bin/bash /bin/sh   USER jovyan   RUN pip install --upgrade pip \   && pip install --upgrade tensorflow \   && pip install --upgrade --no-deps git+git://github.com/keras-team/keras.git \ && pip install --upgrade --no-deps h5py </container>