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Mission: tiny recommender — step 7 of 7

ch 40 · unsupervised learning, embeddings, and recommendersch 40 · unsupervised learning, embeddings, and recommendersch 40 · unsupervised learning, embeddings, and recommendersch 40 · unsupervised learning, embeddings, and recommendersch 40 · unsupervised learning, embeddings, and recommendersch 40 · unsupervised learning, embeddings, and recommendersch 40 · unsupervised learning, embeddings, and recommendersch 40 · unsupervised learning, embeddings, and recommendersch 40 · unsupervised learning, embeddings, and recommendersch 40 · unsupervised learning, embeddings, and recommendersch 40 · unsupervised learning, embeddings, and recommenders7/7
Checkpoint

One last thing before we move on. pass this to mark the lesson done, or skip and keep moving.

Build the hidden-item eval — chapter 21's hide-the-answer habit, recommender edition. For each user (alphabetical order): hide their alphabetically-first item, then recommend from the REMAINING items — recommend_for_user(user, visible) scores every item other users have alongside any visible item (skip the user themselves, count co-occurrences, sort by count then name, exclude the visible items). Print one line per user: f"{user}: hid {hidden!r}, top-2 recs {recs[:2]}, hit={hit}" (hit = hidden item in the top 2), then f"hit rate: {hits}/{len(by_user)}".

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