Realize environment construction for "Deep Learning from scratch" with docker and Vagrant

WHY

The reason why I decided to write this article was that I learned the following books during the year-end and New Year holidays, but there are some parts that get stuck if I am not familiar with Python, so I was able to cut down on mental costs to build an environment and read this book. I was wondering if some people couldn't complete it.

image.png

Deep Learning from scratch-The theory and implementation of deep learning learned from Python

WHAT

The part that I thought was clogged was the visualization of the figure. I use matplotlib to visualize the figure, but there is a trap when building the environment, and if it fits in it, it may take time to solve it.

That's where Docker comes in, where anyone can build the same environment. I have built an environment for docker in Vagrant and use docker, so I have realized an environment completely independent of my personal computer.

The technology used to achieve this is:

These technologies make it easy to carry and understand.

HOW

How to actually do it.

Get the code and move to the code folder

git clone https://github.com/SnowMasaya/deep-learning-excerise.git
cd {Downloaded folder}

Launch Vagrant If you are already using Vagrant, make sure your IP address is unique.

Modify the following part of the Vagrantfile.

config.vm.network "private_network", ip: "{IP address to modify}"
vagrant up

Environment

ansible-playbook -i provisioning/hosts provisioning/site.yml

Get Docker image

docker pull masayaresearch/deep-learning-scratch-excerise

Start Docker and access Docker

docker run -p 8888:8888 -it masayaresearch/deep-learning-scratch-excerise bash

Launch iPython Notebook

ipython notebook --no-browser --port 8888 --ip=*

Access browser

http://192.168.33.25:8888

When the screen below appears, you can see that you can access the ipython notebook.

Screen Shot 2017-01-04 at 8.16.58 AM.png

Please refer to deep-learning-1.ipynb because it actually draws the image.

Screen Shot 2017-01-04 at 8.23.53 AM.png

code

github

https://github.com/SnowMasaya/deep-learning-excerise/blob/master/docker/python/deep-learning-1.ipynb

Docker hub

masayaresearch/deep-learning-scratch-excerise

reference

https://github.com/oreilly-japan/deep-learning-from-scratch

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