Question 1

Which of the following services is specifically designed to provide insights into model predictions by explaining how input features contribute to the final output?

Options :

A : Amazon SageMaker Clarify

B : Amazon SageMaker Feature Store

C : Amazon SageMaker Model Monitor

D : Amazon SageMaker Canvas

Answer: A

Question 2

A company has developed an ML model for image classification. The company wants to deploy the model to production so that a web application can use the model. The company needs to implement a solution to host the model and serve predictions without managing any of the underlying infrastructure. Which solution will meet these requirements?

Options :

A : Use Amazon SageMaker Serverless Inference to deploy the model.

B : Use Amazon CloudFront to deploy the model.

C : Use Amazon API Gateway to host the model and serve predictions.

D : Use AWS Batch to host the model and serve predictions.

Answer: A

Question 3

What is the difference between a machine learning (ML) algorithm and a machine learning (ML) model?

Options :

A : An ML algorithm is used for storing large datasets, whereas an ML model is used for deploying applications

B : An ML algorithm is responsible for the security of the machine learning pipeline, while an ML model manages data preprocessing

C : An ML algorithm is a set of mathematical instructions for solving a specific type of problem, while an ML model is the output of the algorithm after being trained on data

D : An ML algorithm is a pre-trained neural network, while an ML model is the raw data used to train the algorithm

Answer: C

Question 4

A healthcare company is considering migrating its on-premises infrastructure to AWS Cloud to enhance data management, improve scalability, and reduce operational costs. The leadership team is new to cloud technologies and wants a clear understanding of what cloud computing entails, specifically how AWS defines and implements it. This understanding is essential for the company to make informed decisions about the benefits and use cases of cloud computing in their operations.

Given this context, what is cloud computing, as defined by AWS?

Options :

A : Cloud computing involves manually managing physical data centers and networking hardware for data storage and processing

B : Cloud computing is the process of using a single local server to store and process data

C : Cloud computing refers to the on-demand delivery of IT resources and applications via the internet with pay-as-you-go pricing

D : Cloud computing is the practice of using only open-source software for all computing needs

Answer: C

Question 5

How would you differentiate between deep learning and traditional machine learning? (Select two)

Options :

A : Deep learning is a subset of machine learning that uses neural networks with many layers to learn from large amounts of data, while traditional machine learning algorithms often require feature extraction and can use various methods such as decision trees or support vector machines

B : In traditional machine learning, a data scientist manually determines the set of relevant features that the software must analyze, whereas in deep learning, the data scientist gives only raw data to the software and the deep learning network derives the features by itself

C : Traditional machine learning algorithms are only used for supervised learning tasks, whereas deep learning algorithms are only used for unsupervised learning tasks

D : Deep learning models are always faster to train than traditional machine learning models, regardless of the dataset size

E : Deep learning models do not require any data preprocessing, while traditional machine learning models require extensive data preprocessing

Answer: A,B