Learn How To Build Machine Learning Models Faster at KubeCon Amsterdam

KubeCon Amsterdam may be virtual but we’re still here to help you experiment, train, and serve your models faster than ever before.

Learn how to use Kubeflow with a chance to win a motorized scooter!

Win Your Very Own Arrikto Motorized Scooter!

Scooter
Sccoter

Attend our KubeCon sessions and follow on Twitter for a chance to win.

Make sure you check out #kubecon #ml #kubeflow @arrikto on Twitter

Tutorial: From Notebook to Kubeflow Pipelines with HP Tuning: A Data Science Journey

When

Central European Summer Time (CEST / GMT+2)

August 17th – 15:05 – 16:25

US Eastern Daylight Time (EDT / GMT-4)

August 17th – 09:05 – 10:25

US Pacific Daylight Time (PDT / GMT-7)

August 17th – 06:05 – 07:25

How To Attend

Session Details

An introduction to Kubeflow, the ML toolkit for K8s and the workflows you can use as a data scientist to scale up your ML code effortlessly.

Ever thought how hard it is to convert your Jupyter Notebooks into deployable and composable pipelines, scale up computation and run hyperparameter tuning? With Kubeflow, this process becomes extremely easy as you make use of the many components of this ML toolkit: Pipelines, Kale, Katib, Snapshot Store.

You will learn how to deploy Kubeflow in minutes, explore your ML code inside a Jupyter Notebook, convert it to a composable and scalable workflow with the click of a button, make the pipeline reproducible using immutable snapshots, go back in history and debug it, run hyperparameter tuning and distribute your computation.

Did we mention you won’t need any specific SDK or CLI command to do this? Sounds like magic? Come and see for yourself!

Speakers

Ilias Katsakioris

Ilias Katsakioris

Software Engineer

Ilias Katsakioris is a Software Engineer at Arrikto. He holds a Diploma in Electrical and Computer Engineering from the National Technical University of Athens. He is a Kubernetes and Kubeflow enthusiast, and he has been contributing to the Kubeflow project for almost a year. His main Kubeflow contributions are in the area of Data Management and Data Pipelines. Ilias extended the Kubeflow Pipelines DSL to support K8s Persistent Volumes and Volume Snapshots.

Stefano Fioravanzo

Stefano Fioravanzo

Software Engineer

Stefano Fioravanzo is a Software Engineer at Arrikto, his background is in Data Science and ML Research. He understands the value of building robust Machine Learning infrastructure and providing Data Scientist with the necessary tools to scale up their workflows. He works as a full-time contributor to Kubeflow and he is the creator of the Kubeflow Kale project which enables Jupyter Notebooks deployments to Kubeflow Pipelines.

Scooter

WIN ME!

Want to win me?

 

Simply attend one or more of our KubeCon sessions and answer the online quiz on Twitter or LinkedIn. 

Look for #kubecon #ml #kubeflow @arrikto and follow the links.

 

Plenty of swag available too!

Enabling Multi-user Machine Learning Workflows for Kubeflow Pipelines

When

Central European Summer Time (CEST / GMT+2)

August 18th – 14:30 – 15:05

US Eastern Daylight Time (EDT / GMT-4)

August 18th – 08:30 – 09:05

US Pacific Daylight Time (PDT / GMT-7)

August 18th – 05:30 – 06:05

How To Attend

Session Details

Kubeflow is an open source machine learning platform built on Kubernetes. Every service in Kubeflow is implemented either as a Custom Resource Definition (CRD) (e.g., TensorFlow Job) or as a standalone service (e.g., Kubeflow Pipelines).

As enterprises start to adopt Kubeflow, the need for access control, authentication, and authorization is emerging. Kubernetes CRDs come with their own auth story, but what about Services with their own API and database, like Kubeflow Pipelines? In this talk, we explore how we enabled multi-user workflows for Kubeflow Pipelines, in a Kubernetes-native way.

We present how we combined open-source, cloud-native technologies to design and implement a flexible, Kubernetes-native solution for services with their own API and database.

 

The talk will include a live demo.

Speakers

Yannis Zarkadas

Yannis Zarkadas

Software Engineer

Yannis is a software engineer at Arrikto, working with Kubeflow and the Kubernetes sig-storage group. He loves contributing to open source projects and has authored the Cassandra Operator in Rook and the official Scylla Operator, which he is currently maintaining.

Yuan Gong

Yuan Gong

Google Cloud - Software Engineer

I’m a software engineer at Google Cloud working on Kubeflow Pipelines project.

Kubeflow 1.0 Update By A Kubeflow Community Product Manager 

When

Central European Summer Time (CEST / GMT+2)

August 20th – 14:30 – 15:05

US Eastern Daylight Time (EDT / GMT-4)

August 20th – 08:30 – 09:05

US Pacific Daylight Time (PDT / GMT-7)

August 20th – 05:30 – 06:05

How To Attend

Session Details

This session will provide a Kubeflow 1.0 Update by a Kubeflow Community Product Manager. The presentation will include a review of the Kubeflow Community and feature development process, the Kubeflow user survey results, and Kubeflow 1.0 features. The talk will highlight significant business benefits and review use cases from top deployments. It will also include a live demonstration of a workflow to build, train and deploy a versioned Kubeflow Pipeline.

Speaker

Josh Bottom

Josh Bottum

Kubeflow Product Manager and Arrikto Vice President of Community Relations

I am a Kubeflow Community Product Manager and VP at Arrikto. We simplify storage architectures and operations for Kubernetes platforms.

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