Amazon Ubuntu Deep Learning Instance Configuring Steps

  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
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