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Amazon Interview Problems (104)

Problems reported from Amazon data science interviews

Status Title Difficulty
Three Sum Pro Medium
Top K Frequent Elements Pro Medium
Top N Per Group with ROW_NUMBER Pro Medium
Total Spend Per Customer Pro Medium
Beta Distribution Applications Pro Hard
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Coin Change Minimum Pro Hard
Collaborative Filtering Cold Start Pro Hard
Database Indexing with B-Trees Pro Hard
Date-Based Cohort Analysis Pro Hard
Dealing with Data Quality Issues Pro Hard
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Distributed Computing Challenges Pro Hard
Generate Permutations Pro Hard
Hash Map from Scratch Pro Hard
Information Extraction Pipelines Pro Hard
Kernel Density Estimation Pro Hard
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LAG and LEAD for Sequential Comparison Pro Hard
Latest Order Per Customer Using Join and Subquery Pro Hard
Merge K Sorted Lists Pro Hard
Model Drift and Retraining Pro Hard
Model Serving: TorchServe and TF Serving Pro Hard
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Moving Average with Window Frame Pro Hard
Orders Exceeding Customer Lifetime Average Pro Hard
PERCENT_RANK for Distribution Analysis Pro Hard
Revenue Contribution by Region With Rollup Pro Hard
Running Total Pro Hard
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