MLS-C01 Amazon-Web-Services Exam Questions and Free Practice Test

Question 7

An interactive online dictionary wants to add a widget that displays words used in similar contexts. A Machine Learning Specialist is asked to provide word features for the downstream nearest neighbor model powering the widget.
What should the Specialist do to meet these requirements?

A. Create one-hot word encoding vectors.

B. Produce a set of synonyms for every word using Amazon Mechanical Turk.

C. Create word embedding factors that store edit distance with every other word.

D. Download word embedding’s pre-trained on a large corpus.

Correct Answer:A

Question 8

A bank's Machine Learning team is developing an approach for credit card fraud detection The company has a large dataset of historical data labeled as fraudulent The goal is to build a model to take the information from new transactions and predict whether each transaction is fraudulent or not
Which built-in Amazon SageMaker machine learning algorithm should be used for modeling this problem?

A. Seq2seq

B. XGBoost

C. K-means

D. Random Cut Forest (RCF)

Correct Answer:C

Question 9

While reviewing the histogram for residuals on regression evaluation data a Machine Learning Specialist notices that the residuals do not form a zero-centered bell shape as shown What does this mean?
MLS-C01 dumps exhibit

A. The model might have prediction errors over a range of target values.

B. The dataset cannot be accurately represented using the regression model

C. There are too many variables in the model

D. The model is predicting its target values perfectly.

Correct Answer:D

Question 10

An Amazon SageMaker notebook instance is launched into Amazon VPC The SageMaker notebook references data contained in an Amazon S3 bucket in another account The bucket is encrypted using SSE-KMS The instance returns an access denied error when trying to access data in Amazon S3.
Which of the following are required to access the bucket and avoid the access denied error? (Select THREE )

A. An AWS KMS key policy that allows access to the customer master key (CMK)

B. A SageMaker notebook security group that allows access to Amazon S3

C. An 1AM role that allows access to the specific S3 bucket

D. A permissive S3 bucket policy

E. An S3 bucket owner that matches the notebook owner

F. A SegaMaker notebook subnet ACL that allow traffic to Amazon S3.

Correct Answer:ACF

Question 11

A company's Machine Learning Specialist needs to improve the training speed of a time-series forecasting model using TensorFlow. The training is currently implemented on a single-GPU machine and takes approximately 23 hours to complete. The training needs to be run daily.
The model accuracy js acceptable, but the company anticipates a continuous increase in the size of the training data and a need to update the model on an hourly, rather than a daily, basis. The company also wants to minimize coding effort and infrastructure changes
What should the Machine Learning Specialist do to the training solution to allow it to scale for future demand?

A. Do not change the TensorFlow cod

B. Change the machine to one with a more powerful GPU to speed up the training.

C. Change the TensorFlow code to implement a Horovod distributed framework supported by Amazon SageMake

D. Parallelize the training to as many machines as needed to achieve the business goals.

E. Switch to using a built-in AWS SageMaker DeepAR mode

F. Parallelize the training to as many machines as needed to achieve the business goals.

G. Move the training to Amazon EMR and distribute the workload to as many machines as needed to achieve the business goals.

Correct Answer:B

Question 12

A large consumer goods manufacturer has the following products on sale
• 34 different toothpaste variants
• 48 different toothbrush variants
• 43 different mouthwash variants
The entire sales history of all these products is available in Amazon S3 Currently, the company is using custom-built autoregressive integrated moving average (ARIMA) models to forecast demand for these products The company wants to predict the demand for a new product that will soon be launched
Which solution should a Machine Learning Specialist apply?

A. Train a custom ARIMA model to forecast demand for the new product.

B. Train an Amazon SageMaker DeepAR algorithm to forecast demand for the new product

C. Train an Amazon SageMaker k-means clustering algorithm to forecast demand for the new product.

D. Train a custom XGBoost model to forecast demand for the new product

Correct Answer:B
The Amazon SageMaker DeepAR forecasting algorithm is a supervised learning algorithm for forecasting scalar (one-dimensional) time series using recurrent neural networks (RNN). Classical forecasting methods, such as autoregressive integrated moving average (ARIMA) or exponential smoothing (ETS), fit a single model to each individual time series. They then use that model to extrapolate the time series into the future.

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