Thoughtful ML deployments using Explainability
Like Add Share
Kubernetes • May 2021
Thoughtful ML deployments using Explainability
Explore more
Like Add Share
About
Thoughtful ML deployments using Explainability
About

In the talk I show how to make thoughtful ML deployments on Kubernetes. With thoughtful ML deployments I focus on the challenge to keep ML: manageable, accountable and explainable. I propose 5 design principles to achieve this.
The goal of the talk is to show developers that want to move from just creating models to productionizing them using proven best practices to get started. Pointing them both to promising technologies and challenges in a real world ML deployments. While pointing to parallels and differences from proven DevOps practices in traditional software engineering.

Language
English
Level
Intermediate
Length
33 minutes
Type
online conference
About the speaker
About the speaker
Tim Kleinloog
Co-founderDeeploy
Tim Kleinloog is co-founder and technically responsible for the product at Deeploy. Before Tim has worked as a data engineering consultant studying and applying both the data science and computer science of ML. In his work he strives for fair and thoughtful implementations of Machine Learning. At Deeploy he leaves most programming to the dev team, although if he sees an opportunity he likes to play around with Kubernetes and Python.
Details
Language
English
Level
Intermediate
Length
33 minutes
Type
online conference