Question 1

A Machine Learning Specialist is assigned a TensorFlow project using Amazon SageMaker for training, and needs to continue working for an extended period with no Wi-Fi access.

Which approach should the Specialist use to continue working?

Options :

A : Install Python 3 and boto3 on their laptop and continue the code development using that environment.

B : Download the TensorFlow Docker container used in Amazon SageMaker from GitHub to their local environment, and use the Amazon SageMaker Python SDK to test the code.

C : Download TensorFlow from tensorflow.org to emulate the TensorFlow kernel in the SageMaker environment.

D : Download the SageMaker notebook to their local environment then install Jupyter Notebooks on their laptop and continue the development in a local notebook.

Answer: B

Question 2

A Machine Learning Specialist receives customer data for an online shopping website. The data includes demographics, past visits, and locality information. The Specialist must develop a machine learning approach to identify the customer shopping patterns, preferences and trends to enhance the website for better service and smart recommendations.

Which solution should the Specialist recommend?

Options :

A : Latent Dirichlet Allocation (LDA) for the given collection of discrete data to identify patterns in the customer database.

B : A neural network with a minimum of three layers and random initial weights to identify patterns in the customer database

C : Collaborative filtering based on user interactions and correlations to identify patterns in the customer database

D : Random Cut Forest (RCF) over random subsamples to identify patterns in the customer database

Answer: C

Question 3

A data scientist is working on a public sector project for an urban traffic system. While studying the traffic patterns, it is clear to the data scientist that the traffic behavior at each light is correlated, subject to a small stochastic error term. The data scientist must model the traffic behavior to analyze the traffic patterns and reduce congestion.

How will the data scientist MOST effectively model the problem?

Options :

A : The data scientist should obtain a correlated equilibrium policy by formulating this problem as a multi-agent reinforcement learning problem.

B : The data scientist should obtain the optimal equilibrium policy by formulating this problem as a single-agent reinforcement learning problem.

C : Rather than finding an equilibrium policy, the data scientist should obtain accurate predictors of traffic flow by using historical data through a supervised learning approach.

D : Rather than finding an equilibrium policy, the data scientist should obtain accurate predictors of traffic flow by using unlabeled simulated data representing the new traffic patterns in the city and applying an unsupervised learning approach.

Answer: A

Question 4

The Chief Editor for a product catalog wants the Research and Development team to build a machine learning system that can be used to detect whether or not individuals in a collection of images are wearing the company's retail brand The team has a set of training data

Which machine learning algorithm should the researchers use that BEST meets their requirements?

Options :

A : Latent Dirichlet Allocation (LDA)

B : Recurrent neural network (RNN)

C : K-means

D : Convolutional neural network (CNN)

Answer: C

Question 5

A company wants to create an artificial intelligence (Al) yoga instructor that can lead large classes of students. The company needs to create a feature that can accurately count the number of students who are in a class. The company also needs a feature that can differentiate students who are performing a yoga stretch correctly from students who are performing a stretch incorrectly. ...etermine whether students are performing a stretch correctly, the solution needs to measure the location and angle of each student's arms and legs A data scientist must use Amazon SageMaker to ...ss video footage of a yoga class by extracting image frames and applying computer vision models. Which combination of models will meet these requirements with the LEAST effort? (Select TWO.)

Options :

A : Image Classification

B : Optical Character Recognition (OCR)

C : Object Detection

D : Pose estimation

E : Image Generative Adversarial Networks (GANs)

Answer: C,D

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