---
title: 'Learn about MLOps: Kubeflow at OSXP 2022'
description: Are you curious about Kubeflow? Would you like to see a new MLOps demo
  and talk to experts from the field? Meet us at OSXP Paris!
url: https://canonical.com/blog/kubeflow-osxp-2022?format=md
---

1. [Blog](https://canonical.com/blog)
2. Article

---

[Andreea Munteanu](https://canonical.com/blog/author/munteanuandreea "More about Andreea Munteanu")

4 November 2022

# Learn about MLOps: Kubeflow at OSXP 2022

[AI/ML](https://canonical.com/blog/tag/ai-ml)
[Event](https://canonical.com/blog/tag/event)
[Kubeflow](https://canonical.com/blog/tag/kubeflow)
[MLOps](https://canonical.com/blog/tag/mlops)
[Open source](https://canonical.com/blog/tag/open-source)

---

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**When**: 8-9 November 2022

**Where:** Booth E32, OSXP Palais de Congres, Paris

[Open Source Experience](https://www.opensource-experience.com/en/) is the meeting place for the entire open-source software industry. It gathers more than 4,500 professionals, allowing them to deep dive into open-source technologies, solutions and challenges in France and Europe. The event delves into topics like AI/ML,  digital twins and Blockchain. Canonical is going to be present at OSXP Paris 2022, talking about [Charmed Kubeflow](https://charmed-kubeflow.io/), the end-to-end MLOps platform.

[Register now](https://www.opensource-experience.com/en/pre-register/)

## Meet the team at OSXP 2022

Learn about MLOps and how you can kickstart your AI/ML initiatives. Enterprises struggle with data complexity, project complexity, tooling choice and much more. Taking a model from idea to MVP and then from MVP to production comes with different requirements. During the event, you can meet Canonical’s experts and talk about all these and more related topics:

* MLOps
* Charmed Kubeflow: an end-to-end open-source MLOps platform
* Real use-case forMLOps
* Demo of MLOps integration

## A growing MLOps ecosystem

Charmed Kubeflow has multiple components that allow data scientists to develop, train and deploy machine learning models. More than a tool, Canonical is working on building an ecosystem that enables developers to perform optimised training within one tool.

Charmed Kubeflow enables growing MLOps integrations. It offers integrations with various solutions such as MLFlow, for model registry, and Seldon, for inference. During the event, we will demo a new integration. It comes with additional features natively available in Charmed Kubeflow. Are you curious?

[Register now](https://www.opensource-experience.com/en/pre-register/)

#### Learn more about Charmed Kubeflow

* [What is Kubeflow?](https://ubuntu.com/ai/what-is-kubeflow)
* [Hyperparameter tuning](https://ubuntu.com/engage/hyperparameter-tuning-mlops-platform)
* [A guide to ML model serving](https://ubuntu.com/blog/guide-to-ml-model-serving)
* Kubeflow pipelines: [part 1](https://ubuntu.com/blog/data-science-workflows-on-kubernetes-with-kubeflow-pipelines-part-1) & [part 2](https://ubuntu.com/blog/data-science-workflows-on-kubernetes-with-kubeflow-pipelines-part-2)

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