Data scientists desire a self-service, cloud-like experience to access ML modeling tools, data, & compute resources to rapidly build, scale, reproduce, & share ML modeling results with peers & software developers. Open source platforms build on Kubernetes & containers provide desired agility, flexibility, scalability, & portability for data scientists to train, test, & deploy ML models quickly, without IT dependency. The session will provide an overview of containers and Kubernetes, and how these technologies can help solve the challenges faced by data scientists, ML engineers, and application developers. Next, we will review the key capabilities required in a platform to help data scientists easily use technologies like Jupyter Notebooks, ML frameworks, programming languages to innovate faster. Finally, we will share the open-source platform options and the enterprise-level support available. 

Key Takeaways:

  • Containers and kubernetes platforms accelerate ML workflows, and streamline collaboration with software developers;
  • Requirements for an AI platform;
  • Best practices and gotchas around operationalizing containers and kubernetes for ML workflows based on real-world deployments.

Instructors' Bio

Pete Brey, Big Data Solutions at Red Hat

Pete Brey is a deeply experienced Sales and Marketing executive with over 25 years of experience in the technology industry. In his current role at Red Hat, he is responsible for sales and marketing of Big Data solutions focused on Data Analytics, Artificial Intelligence, Machine Learning, and Internet of Things. In this role, Pete helps the world’s largest companies in diverse industries such as financial services, retail, automotive, and telecommunications understand how data can be transformed into information to help them make more accurate and agile decisions to stay ahead of the competition. What sets Pete apart is his breadth of sales and marketing experience coupled with his ability to go deep on a variety of technologies and to crisply explain how technology can solve real world business challenges. The Big Data solutions Pete is developing and selling at Red Hat are based upon Red Hat OpenShift together with Red Hat Ceph massively scalable cloud object storage.


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    Accelerate the AI/ML Lifecycle with an Open Source Platform

    • Webinar Recording