Get behind-the-scenes insights into the world of internal ML platforms and MLOps stack components with Piotr Niedźwiedź and Aurimas Griciūnas in their show, where together with ML platform professionals, they discuss design choices, best practices, and real-world solutions to MLOps challenges.
Brought to you by neptune.ai.
All content for ML Platform Podcast is the property of neptune.ai and is served directly from their servers
with no modification, redirects, or rehosting. The podcast is not affiliated with or endorsed by Podjoint in any way.
Get behind-the-scenes insights into the world of internal ML platforms and MLOps stack components with Piotr Niedźwiedź and Aurimas Griciūnas in their show, where together with ML platform professionals, they discuss design choices, best practices, and real-world solutions to MLOps challenges.
Brought to you by neptune.ai.
Going Deep On Model Serving, Deploying LLMs and Anything Production-Deployment
ML Platform Podcast
42 minutes
1 year ago
Going Deep On Model Serving, Deploying LLMs and Anything Production-Deployment
On this episode of the ML Platform Podcast, Chaoyu Yang discusses the MLOps stack's model serving, model registry and feature store components, online model training, large language model deployment, LLM agents, and more.
ML Platform Podcast
Get behind-the-scenes insights into the world of internal ML platforms and MLOps stack components with Piotr Niedźwiedź and Aurimas Griciūnas in their show, where together with ML platform professionals, they discuss design choices, best practices, and real-world solutions to MLOps challenges.
Brought to you by neptune.ai.
