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السؤال #1
A Machine Learning Specialist wants to determine the appropriate SageMakerVariant Invocations Per Instance setting for an endpoint automatic scaling configuration. The Specialist has performed a load test on a single instance and determined that peak requests per second (RPS) without service degradation is about 20 RPS As this is the first deployment, the Specialist intends to set the invocation safety factor to 0 5 Based on the stated parameters and given that the invocations per instance setting is measur
A. 10
B. 30
C. 600
D. 2,400
عرض الإجابة
اجابة صحيحة: C
السؤال #2
A Data Science team is designing a dataset repository where it will store a large amount of training data commonly used in its machine learning models. As Data Scientists may create an arbitrary number of new datasets every day the solution has to scale automatically and be cost-effective. Also, it must be possible to explore the data using SQL. Which storage scheme is MOST adapted to this scenario?
A. Store datasets as files in Amazon S3
B. Store datasets as files in an Amazon EBS volume attached to an Amazon EC2 instance
C. Store datasets as tables in a multi-node Amazon Redshift cluster
D. Store datasets as global tables in Amazon DynamoDB
عرض الإجابة
اجابة صحيحة: B
السؤال #3
The displayed graph is from a foresting 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
عرض الإجابة
اجابة صحيحة: B
السؤال #4
While working on a neural network project, a Machine Learning Specialist discovers thai some features in the data have very high magnitude resulting in this data being weighted more in the cost function What should the Specialist do to ensure better convergence during backpropagation?
A. Dimensionality reduction
B. Data normalization
C. Model regulanzation
D. Data augmentation for the minority class
عرض الإجابة
اجابة صحيحة: D
السؤال #5
A Machine Learning Specialist is implementing a full Bayesian network on a dataset that describes public transit in New York City. One of the random variables is discrete, and represents the number of minutes New Yorkers wait for a bus given that the buses cycle every 10 minutes, with a mean of 3 minutes. Which prior probability distribution should the ML Specialist use for this variable?
A. Poisson distribution ,
B. Uniform distribution
C. Normal distribution
D. Binomial distribution
عرض الإجابة
اجابة صحيحة: D
السؤال #6
A 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?
A. Bundle the NVIDIA drivers with the Docker image
B. Build the Docker container to be NVIDIA-Docker compatible
C. Organize the Docker container's file structure to execute on GPU instances
D. Set the GPU flag in the Amazon SageMaker CreateTrainingJob request body
عرض الإجابة
اجابة صحيحة: C
السؤال #7
A Machine Learning Specialist is working with a large cybersecurily company that manages security events in real time for companies around the world The cybersecurity company wants to design a solution that will allow it to use machine learning to score malicious events as anomalies on the data as it is being ingested The company also wants be able to save the results in its data lake for later processing and analysis What is the MOST efficient way to accomplish these tasks'?
A. Ingest the data using Amazon Kinesis Data Firehose, and use Amazon Kinesis Data Analytics Random Cut Forest (RCF) for anomaly detection Then use Kinesis Data Firehose to stream the results to Amazon S3
B. Ingest the data into Apache Spark Streaming using Amazon EM
C. and use Spark MLlib with k-means to perform anomaly detection Then store the results in an Apache Hadoop Distributed File System (HDFS) using Amazon EMR with a replication factor of three as the data lake
D. Ingest the data and store it in Amazon S3 Use AWS Batch along with the AWS Deep Learning AMIs to train a k-means model using TensorFlow on the data in Amazon S3
E. Ingest the data and store it in Amazon S3
عرض الإجابة
اجابة صحيحة: A

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