MS Master of Data Science 5

Question 1

In model deployment, what is the purpose of a feature store?

Accepted Answer

To provide a centralized repository for computed features that can be shared across training and serving

Answer

A feature store centralizes feature computation and storage, ensuring consistency between training and inference pipelines and enabling feature reuse across teams.

Question 2

What is the Shapley value used for in explainable AI (XAI)?

Accepted Answer

Quantifying each feature's contribution to a specific prediction fairly across all feature subsets

Answer

Shapley values from game theory fairly attribute prediction contributions to each feature by averaging marginal contributions across all possible feature coalitions.

Question 3

Which sampling strategy should a data scientist use when class imbalance is severe and oversampling the minority class is desired without simple duplication?

Accepted Answer

SMOTE (Synthetic Minority Oversampling Technique)

Answer

SMOTE generates synthetic minority class examples by interpolating between existing minority samples, creating more diverse training data than simple duplication.

Question 4

In distributed computing with Apache Spark, what is a 'shuffle' operation and why is it expensive?

Accepted Answer

Redistributing data across partitions between stages; expensive due to network I/O and disk writes

Answer

A shuffle redistributes data across all executors (e.g., during groupBy or join), requiring extensive network transfer and disk I/O, making it Spark's most costly operation.

Question 5

What is the difference between online learning and batch learning in machine learning?

Accepted Answer

Online learning updates the model incrementally with each new observation; batch learning retrains on the full dataset periodically

Answer

Online (incremental) learning updates model parameters continuously as new data arrives, while batch learning retrains the model from scratch on accumulated data.

MS - Master of Science Practice Test

MS - Master of Science Practice Test

MS Master of Data Science 5