mediumMeta Amazon Databricks

Implement a leakage-safe, stratified train/validation/test split. What can go wrong?

A wrong split quietly inflates every metric you'll ever report, and the bugs are subtle: leaked groups, shuffled time, preprocessing fit on everything. Here is the split done right.

Updated Aug 2026 · Grounded in real Applied AI Engineer interview loops and written to a senior-engineer editorial bar.

A wrong split quietly inflates every metric you'll ever report, and the bugs are subtle: leaked groups, shuffled time, preprocessing fit on everything. Here is the split done right.

Unlock the other 750 answers · ₹2,000 / $25Your progress and mastery stay saved · 6 months · one payment · no auto-renew

UP NEXT ON YOUR JOURNEY

Next in this trackImplement an exponential moving average (EMA) of model weights, and explain why it helps.Next in this trackImplement a learning-rate scheduler with linear warmup and cosine decay.Next in this trackImplement a smoothed n-gram language model and compute perplexity on held-out text.

DISCUSSION · 0

No comments yet — be the first to share your approach.