A Machine Learning Specialist is planning to create a long-running Amazon EMR cluster. The EMR cluster will have 1 master node, 10 core nodes, and 20 task nodes. To save on costs, the Specialist will use Spot Instances in the EMR cluster.
Which nodes should the Specialist launch on Spot Instances?

• A.Master node
• B.Any of the core nodes
• C.Any of the task nodes
• D.Both core and task nodes

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A company is observing low accuracy while training on the default built-in image classification algorithm in Amazon SageMaker. The Data Science team wants to use an Inception neural network architecture instead of a ResNet architecture.
Which of the following will accomplish this? (Choose two.)

• A.Create a support case with the SageMaker team to change the default image classification algorithm to Inception.
• B.Bundle a Docker container with TensorFlow Estimator loaded with an Inception network and use this for model training.
• C.Download and apt-get installthe inception network code into an Amazon EC2 instance and use this instance as a Jupyter notebook in Amazon SageMaker.
• D.Use custom code in Amazon SageMaker with TensorFlow Estimator to load the model with an Inception network, and use this for model training.
• E.Customize the built-in image classification algorithm to use Inception and use this for model training.

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A Data Scientist is building a model to predict customer churn using a dataset of 100 continuous numerical features. The Marketing team has not provided any insight about which features are relevant for churn prediction. The Marketing team wants to interpret the model and see the direct impact of relevant features on the model outcome. While training a logistic regression model, the Data Scientist observes that there is a wide gap between the training and validation set accuracy.
Which methods can the Data Scientist use to improve the model performance and satisfy the Marketing team's needs? (Choose two.)

• A.Add features to the dataset
• B.Add L1 regularization to the classifier
• C.Perform t-distributed stochastic neighbor embedding (t-SNE)
• D.Perform linear discriminant analysis
• E.Perform recursive feature elimination

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Given the following confusion matrix for a movie classification model, what is the true class frequency for Romance and the predicted class frequency for Adventure?

• A.The true class frequency for Romance is 57.92% and the predicted class frequency for Adventure is
  13.12%
• B.The true class frequency for Romance is 0.78 and the predicted class frequency for Adventure is (0.47-
  0.32)
• C.The true class frequency for Romance is 77.56% and the predicted class frequency for Adventure is
  20.85%
• D.The true class frequency for Romance is 77.56% * 0.78 and the predicted class frequency for Adventure is
  20.85%*0.32

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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.Natural Language Toolkit (NLTK) stemming and stop word removal
• B.Amazon SageMaker BlazingText allow mode
• C.Scikit-learn term frequency-inverse document frequency (TF-IDF) vectorizers
• D.Amazon Comprehend syntax analysts and entity detection

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