This quick guide describes the steps to create a Jupyter Notebook on AWS then tunnel into it. This method is preferred since you do not open any additional ports besides 22, requires little-to-no configuration, and is generally more straight-forward.

This current version assumes basic familiarity with cloud computing, AWS services, and Jupyter Notebook. Mostly because this version won't have images and won't dive too deep into each individual step.

1. Log into EC2 console and click "Launch Instance" button.
2. Inside "AWS Marketplace", select the "Deep Learning AMI" from AWS.
3. Select instance type depending on your use case. The "Deep Learning AMI" has support for GPU-backed instance (e.g. g2 and p2) but it's not necessary to use these. Use the cheapest one for your workload (likely memory needed for your dataset).
4. In most cases you can use default settings throughout the rest.
5. Ensure the instance is assigned to a security group with SSH access.
6. Launch your instance

1. SSH into your newly launched instance.
2. Start Jupyter Notebook in the background. Use the --no-browser flag to prevent the server from launching a browser. $ screen $ jupyter notebook --no-browser
3. asdf