Question 1

How do financial institutions use machine learning with mobile check deposits?

Options :

A : To automate logistics

B : To improve ride-sharing apps

C : To reduce wait times

D : To recognize content

Answer: D

Question 2

The Machine Learning Specialist is packaging a custom ResNet model into a Docker container so the company can leverage Amazon SageMaker for training.The Specialist is using Amazon EC2 P3 instances to train the model and needs to properly configure the Docker container to leverage the NVIDIA GPUs.What does the Specialist need to do?

Options :

A : Organize the Docker container-s file structure to execute on GPU instances.

B : Set the GPU flag in the Amazon SageMaker CreateTrainingJob request body.

C : Build the Docker container to be NVIDIA-Docker compatible.

D : Bundle the NVIDIA drivers with the Docker image.

Answer: D

Question 3

How is deep learning different from general machine learning?

Options :

A : It requires no domain knowledge.

B : It uses a layered architecture mimicking the human brain.

C : It relies solely on historical data.

D : It is unrelated to pattern recognition.

Answer: B

Question 4

A Data Scientist is working on an application that performs sentiment analysis.The validation accuracy is poor, and the Data Scientist thinks that the cause may be a rich vocabulary and a low average frequency of words in the dataset.Which tool should be used to improve the validation accuracy?

Options :

A : Natural Language Toolkit (NLTK) stemming and stop word removal

B : Amazon Comprehend syntax analysis and entity detection

C : Amazon SageMaker BlazingText cbow mode

D : Scikit-learn term frequency-inverse document frequency (TF-IDF) vectorizer

Answer: D

Question 5

A company is using Amazon Polly to translate plaintext documents to speech for automated company announcements.However, company acronyms are being mispronounced in the current documents.How should a Machine Learning Specialist address this issue for future documents?

Options :

A : Use Amazon Lex to preprocess the text files for pronunciation.

B : Create an appropriate pronunciation lexicon.

C : Output speech marks to guide in pronunciation.

D : Convert current documents to SSML with pronunciation tags.

Answer: D

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