| Question.11 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? (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. |
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Correct Answer: C
| Question.12 A Machine Learning Specialist is working with a large company to leverage machine learning within its products. The company wants to group its customers into categories based on which customers will and will not churn within the next 6 months. The company has labeled the data available to the Specialist. Which machine learning model type should the Specialist use to accomplish this task? (A) Linear regression (B) Classification (C) Clustering (D) Reinforcement learning |
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Correct Answer: B
| Question.13 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 predicts the trend well, but not the seasonality. (C) The model predicts the seasonality well, but not the trend. (D) The model does not predict the trend or the seasonality well. |
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Correct Answer: A
| Question.14 A company wants to classify user behavior as either fraudulent or normal. Based on internal research, a Machine Learning Specialist would like to build a binary classifier based on two features: age of account and transaction month. The class distribution for these features is illustrated in the figure provided.  Based on this information, which model would have the HIGHEST accuracy? (A) Long short-term memory (LSTM) model with scaled exponential linear unit (SELU) (B) Logistic regression (C) Support vector machine (SVM) with non-linear kernel (D) Single perceptron with tanh activation function |
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Correct Answer: C
| Question.15 A Machine Learning Specialist at a company sensitive to security is preparing a dataset for model training. The dataset is stored in Amazon S3 and contains Personally Identifiable Information (PII). The dataset: ✑ Must be accessible from a VPC only. ✑ Must not traverse the public internet. How can these requirements be satisfied? (A) Create a VPC endpoint and apply a bucket access policy that restricts access to the given VPC endpoint and the VPC. (B) Create a VPC endpoint and apply a bucket access policy that allows access from the given VPC endpoint and an Amazon EC2 instance. (C) Create a VPC endpoint and use Network Access Control Lists (NACLs) to allow traffic between only the given VPC endpoint and an Amazon EC2 instance. (D) Create a VPC endpoint and use security groups to restrict access to the given VPC endpoint and an Amazon EC2 instance |
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Correct Answer: A