GCP AI Fundamentals - AIML Series 5 - ML Enterprise
Introduction In the dynamic realm of machine learning (ML), enterprise workflows form the backbone of innovative solutions. This guide delves into the intricacies of ML enterprise workflows on Google Cloud Platform (GCP), exploring key components such as the Feature Store, Data Catalog, Dataplex, Analytics Hub, and DataPrep. We'll also navigate through custom training practices, hyperparameter tuning with Vertex Vizier, and the essentials of prediction and model monitoring. Buckle up for a witty, casual, and informative ride through the fascinating world of GCP AI fundamentals. ML Enterprise Workflow 1. Data in Enterprise: Feature Store: Definition: A centralized repository for storing, sharing, and managing features. Use Case: Enables reuse of features across different models to ensure consistency and efficiency. Benefits: Reduces redundancy. Streamlines feature management. Improves model performance by using well-defined features. Data Catalog: Definition