Free Amazon MLS-C01 Exam Questions

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?

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

B : wnload 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 : wnload TensorFlow from tensorflow.org to emulate the TensorFlow kernel in the SageMaker environment.

D : wnload 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 data scientist is building a new model for an ecommerce company. The model will predict how many minutes it will take to deliver a package. During model training, the data scientist needs to evaluate model performance. Which metrics should the data scientist use to meet this requirement? (Select TWO.)

A : InferenceLatency

B : Mean squared error (MSE)

C : Root mean squared error (RMSE)

D : Precision

E : Accuracy

Answer: B,C

Question 3

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 : eate one-hot word encoding vectors.

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

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

D : wnload word embedding's pre-trained on a large corpus.

Answer: D

Question 4

A data scientist is building a new model for an ecommerce company. The model will predict how many minutes it will take to deliver a package. During model training, the data scientist needs to evaluate model performance. Which metrics should the data scientist use to meet this requirement? (Select TWO.)

A : InferenceLatency

B : Mean squared error (MSE)

C : Root mean squared error (RMSE)

D : Precision

E : Accuracy

Answer: B,C

Question 5

A Machine Learning Specialist works for a credit card processing company and needs to predict which

transactions may be fraudulent in near-real time. Specifically, the Specialist must train a model that returns the

probability that a given transaction may fraudulent.

How should the Specialist frame this business problem?

A : reaming classification

B : nary classification

C : lti-category classification

D : gression classification

Answer: C