Question 1

What is the primary reason to use PCA (Principal Component Analysis) over t-SNE when visualizing high-dimensional data?

Options :

A : PCA is non-linear while t-SNE is linear

B : PCA is more computationally efficient for large datasets

C : PCA retains local structure while t-SNE focuses on global structure

D : PCA gives a more accurate representation of distances between clusters

Answer: B

Question 2

When using Python to collect data from an API, which of the following statements about OAuth (Open Authorization) is true?

Options :

A : OAuth is only used for basic username and password authentication.

B : OAuth is a protocol used to convert JSON data to XML data.

C : OAuth encrypts the data payload for each API request.

D : OAuth allows users to approve applications to act on their behalf without sharing their password.

Answer: D

Question 3

Which of the following NumPy methods would you use to apply a function element-wise on a 1-D array, while maintaining the shape of the original array?

Options :

A : np.reshape()

B : np.apply_along_axis()

C : np.ravel()

D : np.vectorize()

Answer: D

Question 4

You are implementing an ETL pipeline to fetch data from a JSON-based API and load it into a data lake. The API provides a pagination feature that shows 100 records per page. Which of the following Python libraries is most suitable for performing HTTP requests to extract data from this API?

Options :

A : requests

B : os

C : numpy

D : pandas

Answer: A

Question 5

After performing PCA on a dataset with 10 features, you get two principal components. Which of the following statements is true regarding these components?

Options :

A : Each principal component represents a cluster in the original dataset.

B : Principal components are scaled versions of the original features.

C : Each principal component is a linear combination of the original features.

D : The first principal component is always the most important feature in the original dataset.

Answer: C

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