questions
10 questions across 5 topics
10 questions
- Explain the bias-variance tradeoff and how it affects model selectionML Fundamentalsmedium
- Compare gradient descent variants: SGD, mini-batch, Adam, and learning rate schedulesML Fundamentalsmedium
- Design a recommendation system for a large-scale platformML System Designhard
- Design a feature store for a large ML platformML System Designhard
- How do you implement CI/CD for ML pipelines? How does it differ from software CI/CD?MLOpsmedium
- How do you monitor ML models in production and detect data drift?MLOpsmedium
- Explain the transformer attention mechanism — self-attention, multi-head, positional encodingDeep Learninghard
- Batch Normalization vs. Layer Normalization — what each does and when to use whichDeep Learningmedium
- Common A/B testing pitfalls and how to avoid themStatistics & Probabilitymedium
- Bayesian vs. Frequentist inference — core differences and when each is practicalStatistics & Probabilitymedium