Kubeflow and MLOps Meetup Recap – April 2022

Kubeflow community news

Last week we hosted our fifth “Data Science, Machine Learning and Kubeflow” Meetup. Special thanks to our awesome speakers Yuhui Shi from Convect AI, plus Priya Joseph, Michael Wharton, and Spencer Romo from KUNGFU.AI. In this blog post we’ll recap some highlights from the Meetup and preview what’s next. Ok, let’s dig in.

 

Join a Meetup near you

First, if you missed last week’s Meetup? No need to suffer from FOMO. Here’s a list of the Meetups that are part of the “Data Science, Machine Learning and Kubeflow” Meetup network. Please join the one that is the most time friendly to your location.

 

Thanks for voting for your favorite charity!

With the unprecedented circumstances facing our global community, Arrikto is looking for even more ways to contribute. With this in mind, we thought that in lieu of swag we could give Meetup attendees the opportunity to vote for their favorite charity and help guide our monthly donation to charitable causes. The charity that won this workshop’s voting was UNHCR. The UN Refugee Agency (UNHCR) is a global organization working to save lives, protect rights and build a better future for refugees, internally displaced communities and stateless people. This charity helps ensure that Ukrainians forced to flee their homes are sheltered and safe. We are pleased to be making a donation of $100 to them on behalf of the Kubeflow community. Again, thanks to all of you who attended and voted!

 

Talk #1: Elastic & Automated Time Series Predictive Modeling

Demand modeling is an essential task in supply chain decision making. In this talk you’ll learn how Convect AI utilizes Kubeflow and Kubernetes to automate the model development and deployment of time series predictive tasks, and reduce development cycle time, while boosting model performance.

Yuhui Shi is cofounder of Convect AI — a supply chain decision intelligence as a service company. The company develops “pre-trained” models for supply chain decision tasks such as inventory allocation, warehouse networks, etc.

 

Introducing the Potluck ML Framework

In this presentation, the machine learning team from KUNGFU.AI introduced us to a framework they developed in-house called Potluck. The framework enables you to rapidly scaffold the machine learning lifecycle in a cloud agnostic, data agnostic way. The team will also present on how they are leveraging the latest research for machine learning projects, using examples such as FinRL.

 

KUNGFU.AI is an Austin headquartered (with remote employees all over) artificial intelligence services firm that specializes in building bespoke AI products. Speakers included:

  • Priya Joseph, Principal Machine Learning Engineer
  • Michael Wharton, Principal Machine Learning Engineer
  • Spencer Romo, Principal MLE & Core Contributor to FinRL

 

Lightning Talks

There was also one short lightning talk at the Meetup worth checking out.

 

Upcoming May 2022 Meetup

We are excited to announce that we have our speakers locked in for the next meetup.

 

March 3, 2022

  • Talk #1: Intro to Kubeflow — Jimmy Guerrero @ Arrikto
  • Talk #2: Unlimited Scientific Libraries and Applications in Kubernetes, Instantly! — Guillaume Moutier @Red Hat
  • Talk #3: Experiment Management in Kubeflow — Stephen Oladele @Neptune.ai

 

If you are new to Kubeflow – install MiniKF

MIniKF is the easiest way to get started with Kubeflow on the platform of your choice (AWS or GCP.)

Here’s the links:

 

Get started with Kubeflow – hands-on tutorials

Installed but don’t know where to start? Get started with these hands-on, practical Kubeflow tutorials.

 

FREE Kubeflow courses and certifications

We are excited to announce the first of several free instructor-led and on-demand Kubeflow courses! The “Introduction to Kubeflow” series of courses will start with the fundamentals, then go on to deeper dives of various Kubeflow components. Each course will be delivered over Zoom with the opportunity to earn a certificate upon successful completion of an exam. Visit us to learn more.

We hope to see you at a future Meetup!

 

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