MS-DS Master of Data science Master of Data Science 4

Question 1

Which consistency model guarantees that all nodes in a distributed system see the same data at the same time?

Accepted Answer

Strong (linearizable) consistency

Answer

Strong (linearizable) consistency ensures that all reads reflect the most recent write and all nodes observe updates in the same order.

Question 2

What is the purpose of cross-validation in model evaluation?

Accepted Answer

To obtain a more reliable estimate of model generalization performance

Answer

Cross-validation rotates data through multiple train/validation splits, giving a less biased and lower-variance estimate of how the model will perform on unseen data.

Question 3

Which algorithm is commonly used for collaborative filtering in recommendation systems?

Accepted Answer

Matrix factorization (e.g., SVD)

Answer

Matrix factorization decomposes the user-item interaction matrix into latent factor matrices, capturing hidden preference patterns.

Question 4

In the MapReduce programming model, what does the 'Shuffle and Sort' phase accomplish?

Accepted Answer

It groups all values by key and delivers them sorted to each reducer

Answer

The shuffle and sort phase collects mapper outputs, groups all values associated with the same key, and delivers them sorted to the appropriate reducer.

Question 5

What statistical concept describes the tendency of machine learning models to fit noise in training data rather than the underlying pattern?

Accepted Answer

Overfitting

Answer

Overfitting occurs when a model learns the training data too well, including its noise, resulting in poor generalization to new data.

MS-DS Master of Data science Practice Test

MS-DS Master of Data science Practice Test

MS-DS Master of Data science Master of Data Science 4