Explore a practical guide to building a cutting-edge MLOps deployment platform using Kubernetes, with a focus on deploying deep learning models. Gain valuable insights into integrating key technologies such as NVIDIA Triton Inference Server, Seldon Core v2, Kafka, Prometheus, and Grafana. Learn about an end-to-end workflow for serving complex models like transformers and CNNs, as well as configuring monitoring systems. Discover strategies to enhance model performance, reduce costs, and unlock new use cases in machine learning. This 42-minute conference talk, presented by Andrew Willson, Head of Customer Success at Seldon, at MLOps World: Machine Learning in Production, provides essential knowledge for professionals looking to advance their MLOps capabilities.
Production ML Serving and Monitoring with Kubernetes
MLOps World: Machine Learning in Production via YouTube
Overview
Syllabus
Production ML Serving & Monitoring with Kubernetes
Taught by
MLOps World: Machine Learning in Production
Related Courses
-
Develop Custom Object Detection Models with NVIDIA and Azure Machine Learning
-
Developing Machine Learning Models for Production
-
Production Machine Learning Systems
-
MLOps (Machine Learning Operations) Fundamentals
-
Machine Learning Engineering for Production (MLOps)
-
MLOps Platforms: Amazon SageMaker and Azure ML
