Machine Learning System Design Interview Alex Xu Pdf -

Machine Learning System Design Interview (2023), co-authored by Ali Aminian (part of the ByteByteGo

  • Design a Recommendation System: Covering collaborative filtering, two-tower neural networks, and real-time retrieval vs. ranking.
  • Design a Fraud Detection System: Focuses on imbalanced datasets, feature engineering time windows, and model explainability (SHAP/LIME).
  • Design a Search Engine (Information Retrieval): Covers inverted indexes, learning-to-rank (LTR), and query understanding.
  • Design a Food Delivery ETA (Estimated Time of Arrival) Predictor: Focuses on regression models, geospatial indexing (H3/Uber H3), and dynamic calibration.
  • Design a Video Recommendation System (TikTok/YouTube): Covers the "candidate generation" vs. "ranking" split, and the infamous "cold start" problem.

Which would you like?

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