Welcome

These are the materials for a one-day workshop on MLOps with vetiver on Monday, 18 Sept at posit::conf 2023!

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 DESCRIPTION file
  • To use Python: Install recent versions of Python (3.7 or greater) 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

Julia Silge is a software engineer 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.

Isabel Zimmerman is also 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.

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.