Amazon Ubuntu Deep Learning Instance Configuring Steps


Table of Contents

Headnotes

Many equations and formulas look intimidating. However, when you hunt them down, they are definitely not! Just papertigers!

Now let's hunt the papertiger.
  1. Git server building.
    $ ssh-­keygen -­t rsa ­-C "user.email"

    Modifying hooks:
    $ vim sample.git/hooks/post-receive

    Sample code for hooks:
    #!/bin/sh
    GIT_WORK_TREE=/home/ubuntu/Deployment/sample git checkout -f
    chmod -R 777 /home/ubuntu/Deployment/sample
  2. Install bazel.
    1). Add Bazel distribution URI as a package source (one time setup)

    echo "deb [arch=amd64] http://storage.googleapis.com/bazel-apt stable jdk1.8" | sudo tee /etc/apt/sources.list.d/bazel.list
    curl https://bazel.build/bazel-release.pub.gpg | sudo apt-key add -

    If you want to install the testing version of Bazel, replace stable with testing.2). Install and update Bazel

    sudo apt-get update && sudo apt-get install bazel
    Once installed, you can upgrade to a newer version of Bazel with:

    sudo apt-get upgrade bazel
  3. Tensorflow compiling.
  4. Python module installing.
    • tensorflow
    • numpy
    • pandas
  5. Juypter.
    https://punchagan.muse-amuse.in/posts/create-a-public-jupyter-server-quickly.html

Footnotes

There are many excellent tutorials out there. Some tutorials are too intuitive and it's helpful, but you cannot get it straight on the math details. Some focused on dymestifying math. Some focused on code. I found the best tutorials that give you the conceptual ideas and are possible for implementation without being blind to the math details. Drop a comment if I failed. It would be really appreciable.


If you want to cite this article, please cite this article as:

Lachlan Chen, "Amazon Ubuntu Deep Learning Instance Configuring Steps," in EarnFromScratch, May 31, 2017, https://www.earnfs.com/en/html/113.htm.

or

@misc{lachlanchen2020tutorial,
title=Amazon Ubuntu Deep Learning Instance Configuring Steps,
author={Chen, Lachlan},
year=May 31, 2017
}


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