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NEW QUESTION 36
A trucking company is collecting live image data from its fleet of trucks across the globe. The data is growing rapidly and approximately 100 GB of new data is generated every day. The company wants to explore machine learning uses cases while ensuring the data is only accessible to specific IAM users.
Which storage option provides the most processing flexibility and will allow access control with IAM?

• A. Setup up Amazon EMR with Hadoop Distributed File System (HDFS) to store the files, and restrict access to the EMR instances using IAM policies.
• B. Use a database, such as Amazon DynamoDB, to store the images, and set the IAM policies to restrict access to only the desired IAM users.
• C. Use an Amazon S3-backed data lake to store the raw images, and set up the permissions using bucket policies.
• D. Configure Amazon EFS with IAM policies to make the data available to Amazon EC2 instances owned by the IAM users.

Answer: A

NEW QUESTION 37
When submitting Amazon SageMaker training jobs using one of the built-in algorithms, which common parameters MUST be specified? (Choose three.)

• A. The output path specifying where on an Amazon S3 bucket the trained model will persist.
• B. Hyperparameters in a JSON array as documented for the algorithm used.
• C. The training channel identifying the location of training data on an Amazon S3 bucket.
• D. The IAM role that Amazon SageMaker can assume to perform tasks on behalf of the users.
• E. The Amazon EC2 instance class specifying whether training will be run using CPU or GPU.
• F. The validation channel identifying the location of validation data on an Amazon S3 bucket.

Answer: A,C,E

NEW QUESTION 38
A Machine Learning Specialist is preparing data for training on Amazon SageMaker. The Specialist is using one of the SageMaker built-in algorithms for the training. The dataset is stored in .CSV format and is transformed into a numpy.array, which appears to be negatively affecting the speed of the training.
What should the Specialist do to optimize the data for training on SageMaker?

• A. Transform the dataset into the RecordIO protobufformat.
• B. Use AWS Glue to compress the data into the Apache Parquet format.
• C. Use the SageMaker hyperparameter optimization feature to automatically optimize the data.
• D. Use the SageMaker batch transform feature to transform the training data into a DataFrame.

Answer: A

NEW QUESTION 39
A company is running a machine learning prediction service that generates 100 TB of predictions every day A Machine Learning Specialist must generate a visualization of the daily precision-recall curve from the predictions, and forward a read-only version to the Business team.
Which solution requires the LEAST coding effort?

• A. Run a daily Amazon EMR workflow to generate precision-recall data, and save the results in Amazon S3 Give the Business team read-only access to S3
• B. Generate daily precision-recall data in Amazon QuickSight, and publish the results in a dashboard shared with the Business team
• C. Run a daily Amazon EMR workflow to generate precision-recall data, and save the results in Amazon S3 Visualize the arrays in Amazon QuickSight, and publish them in a dashboard shared with the Business team
• D. Generate daily precision-recall data in Amazon ES, and publish the results in a dashboard shared with the Business team.

Answer: B

NEW QUESTION 40
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. Support vector machine (SVM) with non-linear kernel
• B. Single perceptron with tanh activation function
• C. Logistic regression
• D. Long short-term memory (LSTM) model with scaled exponential linear unit (SELU)

Answer: C

Explanation:
Explanation/Reference: https://machinelearningmastery.com/logistic-regression-for-machine-learning/

NEW QUESTION 41
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