PyData x MunichNLP Vol. 2
About this event
We are back with our second collaborative event with PyData (Vol. 2)! The event will be held in-person at JetBrains Munich, where we will be providing drinks and pizza. Register for the event here.
We have exciting talks from two amazing speakers:
Reproducible ML Workflows & Dev Environments with dstack by Andrey Cheptsov, dstack
Building ML models is an iterative process. Let’s talk about tools and practices that help set up your dev environments and workflows for better productivity and reproducibility?
As a bonus, we’ll have an overview of dstack, an open-source utility that simplifies the MLOps stack, and helps run ML workflows and dev environments in the cloud.
Speaker
Andrey Cheptsov is the creator of dstack. He is passionate about open-source and developer tools for AI. Previously, Andrey worked at JetBrains with the PyCharm team.
Why ML Should be Written as Pipelines from the Get-Go by Hamza Tahir, ZenML
The mechanism through which ML propagates through an organisation from experimentation to production is key to its success. Oftentimes, there is a tendency to break this mechanism into a multi-step process, where experimentation workflows are siloed from their production counter-parts. This “Throw it over the wall” anti-pattern can stunt the velocity of ML teams. In this talk, we talk about why teams should unify this multi-stage process, and give data scientists more agency to exercise control over their production workflows. We’ll also go through a practical demonstration with creating a unified MLOps pipeline with ZenML.
Speaker
Hamza Tahir is a software developer turned ML engineer. An indie hacker by heart, he loves ideating, implementing, and launching data-driven products. His previous projects include PicHance, Scrilys, BudgetML, and you-tldr. Based on his learnings from deploying ML in production for predictive maintenance use-cases in his previous startup, he co-created ZenML, an open-source MLOps framework to build portable production-ready ML pipelines.