AI in Production
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AI in Production

Blueprint of End-to-end Reference Architecture

About the Book

About the Author

Table of Contents

  • AI in Production: Need for a Reference Architecture
    • Introduction
    • The Promise of Machine Learning
    • Ground realities of ML in production
    • Lean Framework for AI in Production
  • ML Opportunity Sizing
    • Introduction
    • Define Business Metric
    • System Feature Metric
    • Solution Requirements
  • Data and Feature Engineering
    • Introduction
    • Data Cleaning
    • Data Transformation
    • Feature Extraction
    • Adjust for data imbalance/skew
  • Model Creation
    • Introduction
    • Select ML Algorithm
    • Model Training & Evaluation
    • Model Tuning
    • Creating Ensembles
  • Introduction
    • Model Deployment Process
    • Monitor Model Predictions
    • Model Management
  • Data Engineering Loop
    • Introduction
    • Data Collection Framework
    • Data Verification
    • Data Pipelines
    • Feature Store
    • Model Explorer: Automated Tuning
    • Model Store
    • Model Serving Infrastructure
    • Model Regression Checker
    • Model Monitoring
    • A/B Testing Analysis
    • Machine Resource Mgt

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