If machine learning (ML)-based analytics is part of your organization's current or future IT strategy, then you need to focus on how to optimize your machine learning operations ("MLOps"). Certainly MLOps is largely about deploying good processes and leveraging deep expertise, but technology can also play a significant role in making ML efforts more effective by enabling machine learning to fully leverage modern architectures such as microservices and cloud-native.
ML is increasingly becoming important for today's business objectives, so it's important to learn from past experience. MLOps is the missing piece that enables your applications to become truly AI-First. Hazelcast and IBM work together to help joint customers deploy successful ML implementations, using popular patterns like microservices and event-driven architectures, in cloud-native environments.
In this webinar, we will cover:
-The challenges of deploying ML models into production that can and should be overcome.
-How Microservices and Cloud-Native create new challenges and new opportunities for ML Ops.
-Recommendations on how to enhance your MLOps practices.
-Key technologies that can help you get more value from ML and allow faster deployments, greater scalability, and greater resilience while -creating smarter, more AI-driven applications.
Please share any of your question below and
register to join here. We hope you can join us on
Monday, February 15th at 10 AM ET. ------------------------------
Matt Rodkey
Program Director Offering Management, IBM Cloud Pak for Multicloud Management
IBM
New London NH
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