Senior Principal Software Engineer
Audrey Reznik
Audrey Reznik has been in the IT industry (private and public sectors) for 27 years in multiple verticals. In the last 4 years, she worked as a Data Scientist at ExxonMobil where she created a Data Science Enablement team to help data scientists easily deploy ML models in a Hybrid Cloud environment. Audrey was instrumental in educating scientists about what the OpenShift platform was and how to use OpenShift containers (images) to organize, run, and visualize data analysis results. Audrey now works as a Data Scientist with the Red Hat OpenShift Data Science Team where she is focused on next-generation applications. She is passionate about Data Science and in particular the current opportunities with ML and Federated Data.
Audrey Reznik's contributions
Article
Why GPUs are essential for AI and high-performance computing
Learn why graphics processing units (GPUs) have become the foundation of artificial intelligence and how they are being used.
Article
Perform inference using Intel OpenVINO Model Server on OpenShift
In this article, you will learn how to perform inference on JPEG images using the gRPC API in OpenVINO Model Server in OpenShift. Model servers play an important role in smoothly bringing models from development to production. Models are served via network endpoints which expose an APIs to run predictions.
Article
Boost OpenShift Data Science with the Intel AI Analytics Toolkit
Intel AI tools save cloud costs, date scientists' time, and time spent developing models. Learn how the AI Kit can help you.
Article
Learn how to build, train, and run a PyTorch model
Once you have data, how do you start building a PyTorch model? This learning path shows you how to create a PyTorch model with OpenShift Data Science.
Article
More machine learning with OpenShift Data Science
Solve the typical data science problems of accessing Amazon S3 data and creating a TensorFlow model by following two new OpenShift Data Science learning paths.
Article
Building machine learning models in the cloud
Get hands-on resources for building machine learning models using Red Hat OpenShift Data Science. Learn how to use NLP, Jupyter notebooks, and more.
Why GPUs are essential for AI and high-performance computing
Learn why graphics processing units (GPUs) have become the foundation of artificial intelligence and how they are being used.
Perform inference using Intel OpenVINO Model Server on OpenShift
In this article, you will learn how to perform inference on JPEG images using the gRPC API in OpenVINO Model Server in OpenShift. Model servers play an important role in smoothly bringing models from development to production. Models are served via network endpoints which expose an APIs to run predictions.
Boost OpenShift Data Science with the Intel AI Analytics Toolkit
Intel AI tools save cloud costs, date scientists' time, and time spent developing models. Learn how the AI Kit can help you.
Learn how to build, train, and run a PyTorch model
Once you have data, how do you start building a PyTorch model? This learning path shows you how to create a PyTorch model with OpenShift Data Science.
More machine learning with OpenShift Data Science
Solve the typical data science problems of accessing Amazon S3 data and creating a TensorFlow model by following two new OpenShift Data Science learning paths.
Building machine learning models in the cloud
Get hands-on resources for building machine learning models using Red Hat OpenShift Data Science. Learn how to use NLP, Jupyter notebooks, and more.
