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NEW QUESTION 33
A Machine Learning Specialist prepared the following graph displaying the results of k-means for k = [1:10]

Considering the graph, what is a reasonable selection for the optimal choice of k?

A. 0
B. 1
C. 2
D. 3

Answer: D

NEW QUESTION 34
A manufacturing company has structured and unstructured data stored in an Amazon S3 bucket. A Machine Learning Specialist wants to use SQL to run queries on this data.
Which solution requires the LEAST effort to be able to query this data?

A. Use AWS Data Pipeline to transform the data and Amazon RDS to run queries.
B. Use AWS Batch to run ETL on the data and Amazon Aurora to run the queries.
C. Use AWS Glue to catalogue the data and Amazon Athena to run queries.
D. Use AWS Lambda to transform the data and Amazon Kinesis Data Analytics to run queries.

Answer: C

NEW QUESTION 35
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 an Amazon SageMaker DeepAR algorithm to forecast demand for the new product
B. Train an Amazon SageMaker k-means clustering algorithm to forecast demand for the new product.
C. Train a custom XGBoost model to forecast demand for the new product
D. Train a custom ARIMA model to forecast demand for the new product.

Answer: D

NEW QUESTION 36
The displayed graph is from a forecasting model for testing a time series.

Considering the graph only, which conclusion should a Machine Learning Specialist make about the behavior of the model?

A. The model predicts both the trend and the seasonality well
B. The model does not predict the trend or the seasonality well.
C. The model predicts the trend well, but not the seasonality.
D. The model predicts the seasonality well, but not the trend.

Answer: B

NEW QUESTION 37
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?

A. Scikit-leam term frequency-inverse document frequency (TF-IDF) vectorizer
B. Amazon SageMaker BlazingText cbow mode
C. Natural Language Toolkit (NLTK) stemming and stop word removal
D. Amazon Comprehend syntax analysis and entity detection

Answer: A
Explanation:
https://monkeylearn.com/sentiment-analysis/

NEW QUESTION 38
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