Question 1

How would you differentiate between K-Means and K-Nearest Neighbors (KNN) algorithms in machine learning?

Options :

A : K-Means is primarily used for regression tasks, while KNN is used for reducing the dimensionality of data

B : K-Means is an unsupervised learning algorithm used for clustering data points into groups, while KNN is a supervised learning algorithm used for classifying data points based on their proximity to labeled examples

C : K-Means is a supervised learning algorithm used for classification, while KNN is an unsupervised learning algorithm used for clustering

D : K-Means requires labeled data to form clusters, whereas KNN does not use labeled data for making predictions

Answer: B

Question 2

Which of the following generative AI techniques are used in Amazon Q Business web application workflow? (Select two)

Options :

A : Retrieval-Augmented Generation (RAG)

B : Large Language Model (LLM)

C : Diffusion Model

D : Variational autoencoders (VAE)

E : Generative adversarial network (GAN)

Answer: A,B

Question 3

A healthcare technology company is developing machine learning models to analyze both structured data, such as patient records, and unstructured data, such as medical images and clinical notes. The data science team is working on feature engineering to extract the most relevant information for the models but is aware that the process differs depending on whether the data is structured or unstructured. To ensure they approach each data type correctly, they need to understand the key differences in feature engineering tasks for structured versus unstructured data in machine learning.

What is a key difference in feature engineering tasks for structured data compared to unstructured data in the context of machine learning?

Options :

A : Feature engineering for structured data focuses on image recognition, whereas for unstructured data, it focuses on numerical data analysis

B : Feature engineering for structured data often involves tasks such as normalization and handling missing values, while for unstructured data, it involves tasks such as tokenization and vectorization

C : Feature engineering for structured data is not necessary as the data is already in a usable format, whereas for unstructured data, extensive preprocessing is always required

D : Feature engineering tasks for structured data and unstructured data are identical and do not vary based on data type

Answer: B

Question 4

Which of the following performance metrics are commonly used to evaluate the effectiveness of a classification system?

Options :

A : Mean Absolute Error (MAE), Root Mean Squared Error (RMSE) and R-squared

B : Bias and Variance

C : Throughput, Latency and Uptime

D : Precision, Recall and F1-Score

Answer: D

Question 5

A company needs a solution that can convert text into human speech so that it can offer audio courses in multiple languages.

Which AWS service is the best fit for this use case ?

Options :

A : Amazon Comprehend

B : Amazon Lex

C : Amazon Translate

D : Amazon Polly

Answer: D

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