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## ubuntu_vm_customizations.md

      
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              January 5, 2018 05:04
            
              
                Setting up Ubuntu Vitrual Machine on Windows 10 64-bit host PC
              
          
Install Sublime Text editor: http://tipsonubuntu.com/2017/05/30/install-sublime-text-3-ubuntu-16-04-official-way/


## jupyter_notebook_w_nohup.md

      
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              April 9, 2024 08:56
            
              
                Jupyter notebook with nohup
              
          
    Running jupyter notebook with nohup

This is helpful when running jupyter notebook on remote server (AWS) and tunneling into it,
because with nohup the notebook process continues to run on the server
even if you get disconnected from it (any running notebook code continues to run on the server
without interruption, and just needs to be re-tunneled into).
Start jupyter notebook on remote server

In the remote server terminal, run:
nohup jupyter notebook &amp;


## commit_jupyter_notebooks_code_to_git_and_keep_output_locally.md

      
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                / commit_jupyter_notebooks_code_to_git_and_keep_output_locally.md
            
            
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              January 12, 2025 13:42
            
              
                How to commit jupyter notebooks without output to git while keeping the notebooks outputs intact locally
              
          
    Commit jupyter notebooks code to git and keep output locally


Add a filter to git config by running the following command in bash inside the repo:

git config filter.strip-notebook-output.clean 'jupyter nbconvert --ClearOutputPreprocessor.enabled=True --to=notebook --stdin --stdout --log-level=ERROR'  


Create a .gitattributes file inside the directory with the notebooks


Add the following to that file:


## render_plotly_in_jupyterlab_on_sagemaker.py
from IPython.display import HTML
import plotly.express as px

# Create Plotly fig objects in plotly as usual, and then use HTML(fig.to_html()) to render them in Jupyterlab on SageMaker.
# Or just write to html file: fig.write_html("fig.html") and view it.
	from IPython.display import HTML
	import plotly.express as px

	# Create Plotly fig objects in plotly as usual, and then use HTML(fig.to_html()) to render them in Jupyterlab on SageMaker.
	# Or just write to html file: fig.write_html("fig.html") and view it.