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The AWS Machine Learning Specialty certification is designed for developers and data scientists who want to enhance their skills in using machine learning via the AWS platform.
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Amazon AWS Certified Machine Learning - Specialty Sample Questions (Q137-Q142):
NEW QUESTION # 137
A Machine Learning Specialist is preparing data for training on Amazon SageMaker The Specialist 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. Use the SageMaker batch transform feature to transform the training data into a DataFrame
- B. Transform the dataset into the Recordio protobuf format
- C. Use the SageMaker hyperparameter optimization feature to automatically optimize the data
- D. Use AWS Glue to compress the data into the Apache Parquet format
NEW QUESTION # 138
A Machine Learning Specialist is training a model to identify the make and model of vehicles in images The Specialist wants to use transfer learning and an existing model trained on images of general objects The Specialist collated a large custom dataset of pictures containing different vehicle makes and models
- A. Initialize the model with pre-trained weights in all layers and replace the last fully connected layer.
- B. Initialize the model with random weights in all layers and replace the last fully connected layer
- C. Initialize the model with random weights in all layers including the last fully connected layer
- D. Initialize the model with pre-trained weights in all layers including the last fully connected layer
NEW QUESTION # 139
A Machine Learning Specialist must build out a process to query a dataset on Amazon S3 using Amazon Athena The dataset contains more than 800.000 records stored as plaintext CSV files Each record contains 200 columns and is approximately 1 5 MB in size Most queries will span 5 to 10 columns only How should the Machine Learning Specialist transform the dataset to minimize query runtime?
- A. Convert the records to Apache Parquet format
- B. Convert the records to XML format
- C. Convert the records to JSON format
- D. Convert the records to GZIP CSV format
NEW QUESTION # 140
An interactive online dictionary wants to add a widget that displays words used in similar contexts. A Machine Learning Specialist is asked to provide word features for the downstream nearest neighbor model powering the widget.
What should the Specialist do to meet these requirements?
- A. Produce a set of synonyms for every word using Amazon Mechanical Turk.
- B. Create word embedding factors that store edit distance with every other word.
- C. Create one-hot word encoding vectors.
- D. Download word embedding's pre-trained on a large corpus.
NEW QUESTION # 141
A Machine Learning Specialist is building a model that will perform time series forecasting using Amazon SageMaker The Specialist has finished training the model and is now planning to perform load testing on the endpoint so they can configure Auto Scaling for the model variant Which approach will allow the Specialist to review the latency, memory utilization, and CPU utilization during the load test"?
- A. Generate an Amazon CloudWatch dashboard to create a single view for the latency, memory utilization, and CPU utilization metrics that are outputted by Amazon SageMaker
- B. Build custom Amazon CloudWatch Logs and then leverage Amazon ES and Kibana to query and visualize the data as it is generated by Amazon SageMaker
- C. Review SageMaker logs that have been written to Amazon S3 by leveraging Amazon Athena and Amazon OuickSight to visualize logs as they are being produced
- D. Send Amazon CloudWatch Logs that were generated by Amazon SageMaker lo Amazon ES and use Kibana to query and visualize the log data.
NEW QUESTION # 142
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