Day 61 of 133

CI/CD for ML (CD4ML) + DSA 1-D DP

Code + data + model + deployment pipelines; tests for ML.

DSA · NeetCode 1-D DP

House RobberDSA · 1-D DP
Interview questions to prep
1. State the DP: rob(i) = max(rob(i-1), rob(i-2) + nums[i]).
2. Generalize to house-robber-ii (circular street) — what's the trick?
House Robber IIDSA · 1-D DP
Interview questions to prep
1. State the DP: define the state, the transition, and the base case explicitly.
2. Top-down (memoized recursion) vs bottom-up (tabulation) — which is more natural here, and why?
3. Can you space-optimize from O(n) to O(1)? Show the rolling-window trick.

CI/CD pipelines: code, data, model, deploymentMLOpsMartin Fowler
Interview questions to prep
1. How does CI/CD for ML differ from traditional CI/CD?
2. What are the four levels of MLOps maturity (Google's framing)?
Testing ML systems: unit, integration, model, dataMLOpsEugene Yan
Interview questions to prep
1. What kinds of tests do you write specifically for ML code?
2. What is a behavioral test (CheckList) for an NLP model?
Shadow deployments & blue/green for MLMLOpsMartin Fowler
Interview questions to prep
1. Compare shadow, canary, and blue/green deployments for ML.
2. What's the operational cost of running a shadow deployment for weeks before you cut over?

References & further reading