Abstract: 

Data scientists desire a self-service, cloud-like experience to access machine learning modeling tools, data, and compute resources to rapidly build, scale, reproduce, and share ML modeling results with peers. Software developers want to streamline the process of integrating the ML models into application development. Red Hat and CognitiveScale have joined forces to bring integrated ML and DevOps tools to hybrid and multi-cloud platforms to provide the capabilities that data scientists and software developers need to securely build and deploy AI/ML-powered intelligent software applications in a consistent way across data centers, public clouds, and the edge.

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.

In this workshop, we will dive into the CognitiveScale Certifai solution on Red Hat OpenShift Kubernetes Platform and demonstrate how to increase the trust of your machine learning models by evaluating fairness/bias, robustness, explainability, accuracy, compliance, and data quality. We will show how to accelerate delivering AI/ML workflows by identifying and resolving model problems before pushing them to production.

Prerequisites & Setup:
Python,
Jupyter,
Cortex Certifai Toolkit
https://github.com/CognitiveScale/cortex-certifai-workshop/blob/master/odsc-boston-15-april-2020/README.md

Bio: 

Coming Soon!