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hardGoogleScale AIDatabricks

Deduplicate near-identical documents in a huge corpus. Implement MinHash for fast similarity.

Comparing every pair of a million documents is a trillion comparisons. MinHash estimates Jaccard similarity from a tiny signature, and LSH turns dedup into a near-linear scan. Here is the implementation.

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

Comparing every pair of a million documents is a trillion comparisons. MinHash estimates Jaccard similarity from a tiny signature, and LSH turns dedup into a near-linear scan. Here is the implementation.

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Next in this trackImplement top-k and top-p (nucleus) sampling from a model's next-token logits.Next in this trackImplement Rotary Position Embedding (RoPE) applied to query and key vectors.Next in this trackImplement a leakage-safe, stratified train/validation/test split. What can go wrong?
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