Red Hat & CogScale
Accelerate AI/ML Workflows
in Hybrid Cloud

Wednesday, April 1, 2020

Accelerate AI/ML Workflows in Hybrid Cloud with Red Hat and CogScale



April 15th 11_00 AM- 12_30 PM EST 


Red Hat Open Shift and CognitiveScale are inviting you to join us Wednesday, April 15th for our workshop at the virtual ODSC Conference.
In this workshop, we will dive into the CognitiveScale Certifai solution on Red Hat OpenShift Kubernetes Platform and we will explain how to accelerate AI adoption by removing transparency and trust as barriers for moving AI from development into production, reducing human labor required to manually detect, score and correct risks within black-box models and reduce residual business risks from deployment of black-box automated decisioning systems.

Certifai boosts data scientist productivity, while protecting your business with brand insurance and successful AI risk management. This combination creates an AI Trust Index.

Your team can interact with the workshop by downloading the Certifai toolkit before the workshop begins and discover how to mitigate project stall, improve transparency and robustness in models, and begin to remove bias from your automated decisions.

How to Interact

Sign up for this event and mark your calendar for April 15th at 11am EST.
Download the Certifai Toolkit here.

Join us for the live interaction! 

ODSC East 2020 is one of the largest applied data science conferences in the world. The speakers include core contributors to many open source libraries and languages. Attend ODSC Virtual Event and learn the latest AI & data science topics, tools, and languages from some of the best and brightest minds in the field. CognitiveScale’s Certifai builds trust into digital systems by detecting and scoring black-box model risks. Cortex Certifai generates the first-ever composite trust score, the AI Trust Index. Certifai can be applied to any black-box model including machine learning models, statistical models, business rules, and other predictive models and works with a variety of input data.

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