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I will also show how to setup two bash commands to make the whole process easier. In this post I will show you how to run a Jupyter notebook on a remote server and how to access it on your laptop. Although this workflow certainly allows you to run your code on the remote server, you can no longer use Jupyter Notebook to, e.g., experiment with your models and visualize your results interactively. You could even set up the experiment in a notebook and export the notebook to a script using jupyter nbconvert -to script your_notebook.ipynb. If you are in this situation, you can set up your experiment by writing a Python script on your laptop, run it on a small subset of your data to verify that it can run, copy it to a remote server, and execute it from the command line. You can use remote desktop software to access the remote server and otherwise use Jupyter Notebook as your normally would on your laptop. If your remote server has a Graphical User Interface (GUI), you are in luck. Luckily, you may be in the situation where you have these resources available on a remote server! Maybe you’re running graph convolutional networks on large graphs or doing machine translation with recurrent neural networks on large text corpora and need some more CPU cores, RAM, or a couple of GPUs. However, if you’re working with large datasets, doing computationally expensive data processing, or learning complex models you probably need something more powerful than a laptop extra power. In many cases, running a Jupyter notebook on a laptop or work station is sufficient.

As a tool, Jupyter Notebook can enhance productivity by making it easier to perform data analysis, model prototyping, and experiments in an interactive way, thus shortening the feedback loop from coding and seeing results. Jupyter Notebook is a staple tool in many data scientists’ toolkit.

Open in terminal killed silently in vnc