Welcome
These are the materials for a one-day workshop on MLOps with vetiver on Monday, 12 Aug at posit::conf 2024!
Many data scientists understand what goes into training a machine learning or statistical model, but creating a strategy to deploy and maintain that model can be daunting. In this workshop, learn what MLOps (machine learning operations) is, what principles can be used to create a practical MLOps strategy, and what kinds of tasks and components are involved. We’ll use vetiver, a framework for MLOps tasks in Python and R, to version, deploy, and monitor the models you have trained and want to deploy and maintain in production reliably and efficiently.
Is this workshop for me?
We expect participants to have exposure to basic modeling and machine learning practice, but NOT expert familiarity with advanced ML or MLOps topics. This workshop is for you if you:
- have intermediate R or Python knowledge (this will be a “choose your own adventure” workshop where you can work through the exercises in either R or Python)
- can read data from CSV and other flat files, transform and reshape data, and make a wide variety of graphs
- can fit a model to data with your modeling framework of choice
Preparation
We will provide an environment with Posit Workbench and Posit Connect available, but you also have the option to work locally on your laptop rather than on Posit Workbench. If this is your preference, please come to the workshop with your laptop already set up.
- Clone the repo so you have the files and data locally
- To use R: Install recent versions of R and RStudio, along with the packages outlined in our
DESCRIPTIONfile - To use Python: Install Python 3.10 and your preferred IDE, along with the packages outlined in our
requirements.txt. - Optionally, install Docker Desktop
Join us on GitHub Discussions to ask questions and share ideas.
Schedule
Quarto files for working along are available on GitHub.
| Time | Activity |
|---|---|
| 09:00 - 10:30 | Introduction |
| 10:30 - 11:00 | Coffee break |
| 11:00 - 12:30 | Deploy your model |
| 12:30 - 13:30 | Lunch break |
| 13:30 - 15:00 | Deeper into deployment |
| 15:00 - 15:30 | Coffee break |
| 15:30 - 17:00 | Monitor your model |
Instructors
Isabel Zimmerman is a software engineer on the open source team at Posit PBC, where she works on building MLOps frameworks. When she’s not geeking out over new data science techniques, she can be found hanging out with her dog or watching Marvel movies.
Julia Silge is an engineering manager at Posit PBC focusing on open source MLOps tools, as well as an author and international keynote speaker. Julia loves making beautiful charts, Jane Austen, and her two cats.
Acknowledgments
This website, including the slides, is made with Quarto. Please submit an issue on the GitHub repo for this workshop if you find something that could be fixed or improved.
Reuse and licensing
This work is licensed under a Creative Commons Attribution 4.0 International License.