Design a Machine Learning Platform — System Design Interview Practice
Design an ML platform that trains custom models, automates ML workflows, deploys models as APIs, and monitors model performance in production. Work through the requirements, architecture trade-offs, and an interactive design review.
Requirements and concepts to consider
- Train custom ML modelsRequirement
- Use AutoML for quick prototypesRequirement
- Deploy models as endpointsRequirement
- Perform batch predictionsRequirement
- Monitor model performanceRequirement
- Version control for modelsRequirement
- Implement CI/CD for MLRequirement
- Explain model predictionsRequirement
- gcpConcept to explore
- vertex aiConcept to explore
- automlConcept to explore
- machine learningConcept to explore
- mlopsConcept to explore