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This course provides a technical overview of the machine learning lifecycle, covering data preparation, feature engineering, feature stores, model training and tuning, deployment and monitoring, and inference or model serving.
Syllabus
Video Start
Content intro
Motivation to this video
Stage 1: Data Preparation
Data Preparation - Feature Engineering
Data Preparation - Feature Store
Data Preparation - Data Artifacts
Stage 2: Model Training and Tuning
Stage 3: Model Deployment and Monitoring
Model Deployment and Monitoring - Online Feature Store
Model Deployment and Monitoring - MLI
Recap
Credits
Taught by
Prodramp