A Deep Dive into Machine Learning Pipeline with ML Ops architecture, Model registry, and Feature Store

  1. ML Training platform with AutoML, stacking, blending
  2. ML Observability and monitoring
  3. Model Registry
  4. Model Transformation
  5. Feature Store
  • (00:00) Video starts
  • (00:08) Content intro
  • (03:26) Deep Dive Starts
  • (04:28) Data Preparation and Pre-processing
  • (08:55) Machine Learning Frameworks
  • (13:00) ML Training Frameworks
  • (15:56) Statistical ML and Deep Learning
  • (20:00) AutoML & Blending/Stacking
  • (27:56) ML Ops Platforms
  • (31:15) MLOps Architecture
  • (36:00) Model Registry
  • (40:07) Model Transformation (ONNX)
  • (43:12) Data, Code, and Model Artifacts
  • (47:42) Feature Store
  • (55:05) Recap

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