Accelerate innovation in the enterprise with distributed ML and DL (sponsored by BlueData)
Nanda Vijaydev shares practical examples ofand lessons learned fromML/DL use cases in financial services, healthcare, and other industries. You'll learn how to quickly deploy containerized multinode environments for TensorFlow and other ML/DL tools in a multitenant architecture either on-premises, in the cloud, or in a hybrid environment.
| Talk Title | Accelerate innovation in the enterprise with distributed ML and DL (sponsored by BlueData) |
| Speakers | Nanda Vijaydev (BlueData) |
| Conference | O’Reilly Artificial Intelligence Conference |
| Conf Tag | Put AI to Work |
| Location | New York, New York |
| Date | April 16-18, 2019 |
| URL | Talk Page |
| Slides | Talk Slides |
| Video | |
How do you accelerate innovation and deliver faster time to value for your AI initiative while ensuring enterprise-grade security and high performance? How do you provide easy access to the tools and data your data science teams need for large-scale distributed ML/DL with greater agility for rapid prototyping and iteration? Nanda Vijaydev shares practical examples of—and lessons learned from—ML/DL use cases in financial services, healthcare, and other industries. You’ll learn how to quickly deploy containerized multinode environments for TensorFlow and other ML/DL tools in a multitenant architecture either on-premises, in the cloud, or in a hybrid environment.
