Machine learning (ML) is the study and development of algorithms that improves with use of data. As it deals with the training data, the machine algorithm changes and grows over time. Most ML models begin with “training data” which the machine processes and begins to “understand” statistically. These learning models are resource intensive and demand a significant amount of processing power that can negatively impact performance.
On March 9, 2023, experts from the FCIA will dive into this topic at our live webcast “Benefits of FC-NVMe for Containerized ML Models.” In this session, you’ll learn the benefits of containerizing ML models with NVMe over Fibre Channel (FC-NVMe). FC-NVMe is an extension of the NVMe™ network protocol to Fibre Channel delivering faster and more efficient connectivity between storage and servers and providing the highest throughput and fastest response times. This webcast will include:
- An overview of containers using Docker
- Machine learning fundamentals
- Machine learning/deep learning storage access requirements
- Advantages of FC-NVMe for ML
- Containerized ML models using FC-NVMe
Register here and bring your questions. Our experts will be ready to answer them.
We look forward to seeing you on March 9th.
