The Jupyter notebooks in this project are intended to walk you through each phase of the machine learning workflow - data understanding and exploration, data cleaning, feature engineering, and model training. So going through these notebooks step-by-step is a great way to get started with the project.
To make the notebooks reproducible and executable by everyone, we have containerized and deployed them on the public JupyterHub instance on the Massachusetts Open Cloud (MOC). So you can get access to a Jupyter environment and run our notebooks in just a few clicks! To do so, please follow the steps below:
- Visit our JupyterHub, click on
Log in with moc-ssoand sign in using your Google Account.
- On the spawner page, select
Ceph Hard Drive Failure Predictionfor notebook image,
Largefor container size, and then click
Start serverto spawn your server.
- Once your server has spawned, you should see a directory titled
ceph-drive-failure-<current-timestamp>. All the notebooks should be available inside the
notebooksdirectory in it for you to explore.
In addition to exploring the notebooks, you can also read our blog post to get a brief summary of the project. Or check out our conference talk at DevConf.CZ 2020 for an in-depth presentation and discussion.