Learn how Intel and RedHat have partnered together to enable Intel’s most popular AI developer optimizations on RedHat OpenShift Data Science. Utilize the power of drop-in acceleration for popular frameworks such as Scikit-Learn, TensorFlow and Pandas without complex installations or Kubernetes set-up by using Intel® oneAPI AI Analytics Toolkit on RedHat OpenShift Data Science for a simple developer experience. The audience will learn RedHat and Intel’s technical implementation behind the significant performance speed-up that users gain with these optimizations on RedHat’s new flexible hybrid cloud experience.
Visit Intel® oneAPI AI Analytics Toolkit (AI Kit) for more details and up-to-date product information https://software.intel.com/content/www/us/en/develop/tools/oneapi/ai-analytics-toolkit.html
Intel® oneAPI AI Analytics Toolkit Release Notes https://software.intel.com/content/www/us/en/develop/articles/oneapi-ai-analytics-toolkit-release-notes.html
Download AI Kit from Intel https://software.intel.com/content/www/us/en/develop/tools/oneapi/ai-analytics-toolkit/download.html?operatingsystem=linux or Red Hat Marketplace https://marketplace.redhat.com/en-us/products/ai-analytics-toolkit
Intel® oneAPI AI Analytics Toolkit Installation Guide https://software.intel.com/content/www/us/en/develop/articles/installation-guide-for-intel-oneapi-toolkits.html
Utilize the Intel® oneAPI AI Analytics Toolkit Getting Started Guide https://software.intel.com/content/www/us/en/develop/documentation/get-started-with-ai-linux/top.html
Intel® oneAPI AI Analytics Toolkit Code Samples https://software.intel.com/content/www/us/en/develop/documentation/get-started-with-ai-linux/top.html
Machine Learning & Analytics Blogs https://medium.com/intel-analytics-software
Intel AI Blog site https://www.intel.com/content/www/us/en/artificial-intelligence/blog.html
Webinars & articles https://techdecoded.intel.io/topics/data-science/
Ask questions and share information with others through the Community Forum https://community.intel.com/t5/Intel-AI-Analytics-Toolkit/bd-p/ai-analytics-toolkit
Discuss with experts at AI Frameworks Forum https://community.intel.com/t5/Intel-Optimized-AI-Frameworks/bd-p/optimized-ai-frameworks
Rachel is an AI Technical Consulting Engineer who helps customers optimize their workflows with data analytics and machine learning algorithms from Intel. She holds a bachelor’s degree in Computer Science and Data Science from the College of William & Mary with a background in geospatial analysis.
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 Data Science Team where she is focused on the Red Hat OpenShift Data Science platform. She is passionate about Data Science and in particular the current opportunities with ML and Federated Data.
Karl Eklund is a Principal Architect aligning customer goals to solutions provided by the open source community and commercial vendors within the Red Hat OpenShift Data Science platform. Prior to joining Red Hat, Karl advised technology leaders on their Enterprise Data Strategies and worked alongside academic researchers in a traditional High Performance Computing environment.