AI in Production
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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