ML-System-Design

Learning Notes from System Design and Algorithm Lecture Series.

1. Define Project Objectives
2. Data Curation
3. Exploratory Data Analysis (EDA)
4. Model and KPI Selection
5. Model Training
6. Evaluation
7. Interpetations & Insights
8. Batch Prediction, Model Monitoring and Maintenance

Roadmap

Resources

• End-to-end ML OPs Architecture
• Stanford CS 329S: Machine Learning Systems Design