Dive into a comprehensive workshop that explores the implementation of machine learning pipelines using Kubeflow, Feast, and Kafka in Google Cloud Platform (GCP). Learn how to set up a classification problem framework, leveraging Kubernetes and Docker for efficient deployment. Discover the intricacies of data feature store management with Feast and explore serving endpoints using KF Serving. Gain hands-on experience in monitoring model performance through Grafana and master the art of making API calls for prediction endpoints, handling both real-time Kafka data and batch data. This 1-hour 48-minute session, led by Aniruddha Choudhury, a Senior Data Scientist at Publicis Sapient with extensive experience in AI development solutions, offers valuable insights into productionizing machine learning models in a cloud environment.
Productionize with Kubeflow Orchestration and Feast in GCP - Workshop
MLOps World: Machine Learning in Production via YouTube
Overview
Syllabus
Workshop Sessions: Productionize with Kubeflow Orchestration with Feast in GCP
Taught by
MLOps World: Machine Learning in Production
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