Remote jupyter notebook can be useful when the remote computer has better computing power than the local one or the remote is a server that you can connect from different places.

Prepare

• First, you need to have openssh server installed on the remote machine.
• You will need to generate public key authentication on our local machine.
• In the remote machine, copy the content of id_rsa.pub to ~/.ssh/authorized_keys (reference link)
• Test ssh without typing the password

  $ssh <username>@<remoteIP>
  

• In the remote machine, install anaconda or miniconda
• Create a deeplearning env (optional) using conda
• Activate deeplearning env, and install jupyter notebook (reference)
• Configure Jupyter to use Python kernel

  ipython kernel install --user --name=deeplearning
  

• In the remote machine, add PATH for jupyter notebook in ~/.bashrc file. I am using the path in miniconda.

  export PATH="/home/leiming/miniconda3/envs/deeplearning/bin:$PATH"
  

Test

• Now, from your local machine, you can ssh to remote.

• Start jupyter notebook via port 8889 in the remote machine. (Do not close the current terminal!)

  jupyter notebook --no-browser --port 8889
  

• Start a new terminal in your local terminal

  ssh -N -L localhost:8899:localhost:8889 <username>@<remoteIP>
  

• Copy the localhost link (from the remote machine terminal) to your browser in your local machine

  http://localhost:8889/?token=dd5ac17bc80e068ece002ea35ccf867547030cfa0328
  

• Now, you should see your brower has a jupyter notebook with the default deeplearning conda env.