Press Release

Iguazio MLOps Platform Now Supports Amazon FSx for NetApp ONTAP

MLOps for Good
Hackathon

Join us for the first-ever MLRun hackathon, to help bring data science to production for social Good.

Iguazio will be donating $10 to charity for every participant.

MLOps for Good
Hackathon

Join us for the first-ever MLRun hackathon, to help bring data science to production for Good.

Iguazio will be donating $10 to X for every participant.

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Purpose & Prizes

AI can be used to make an impact in so many fields, from detecting fake news to advancing healthcare in times of pandemic. But the long path to production prevents these innovations from making immediate real-world impact.

That’s why we decided to start the ‘MLOps for Good’ Hackathon, aimed at leveraging MLOps best practices to further causes that we all care about, immediately.

Apart from the great impact your innovations will achieve, we will also donate $10 to charity for every participant, and reward the winning teams for their efforts:

1st Place

iPhone 12 for the entire team (up to 8)

2nd place

airpods for team

3rd Place

$150 Amazon gift cards for the team

Example Project Categories

Detecting Online Forgeries and Fake News

Online fakes and forgeries are growing at a staggering pace, and this trend influences all of lives adversely, and specifically an area near and dear to all our hearts – trusting the data.  What innovations and analyses can we provide in the area of identifying and preventing increasingly complex and difficult to detect online fakes and forgeries?

Optimizing Testing and Prediction of Illness

Due to COVID-19 many people who require routine testing & screening have not been able to have access to regular healthcare due to restrictions and the load on regular care services.  How can ML be leveraged to triage those in need of the most urgent screening, testing and care, for Coronavirus and other illnesses, and how can we do a better job at predicting the impact on developing illness?

Improving Child Safety on the Web

Children have been exposed to much more online content during the pandemic due to lockdown constraints, whether videos, pictures, applications, and more, many times being targeted by online predators and inappropriate content.  How can machine learning help to identify unsafe digital activities and content for children?

How to Get Started

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First you’ll need to join the MLOps Live Slack Community.
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Submit your project name & primary contact (will be live 24th of May).

Check out the projects already submitted HERE.

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Follow this guide to get started with MLRun.

We have MS Azure resources for cloud run projects, or you can host your own…
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Show your support for MLRun by giving us a  on

Project Criteria

Big Thanks to Our Partners

Community Partners

Join the community

MLRun is an open-source project. To discuss or get help, please join us!