Machine Learning Specialty (Page 29)

A data scientist uses Amazon SageMaker Data Wrangler to obtain a feature summary from a dataset that the data scientist imported from Amazon S3.The data scientist notices that the prediction power for a dataset feature has a score of 1.What is the cause of the score?Read More →

A company’s machine learning (ML) team needs to build a system that can detect whether people in a collection of images are wearing the company’s logo.The company has a set of labeled training data.Which algorithm should the ML team use to meet this requirement?Read More →

A company wants to use machine learning (ML) to improve its customer churn prediction model.The company stores data in an Amazon Redshift data warehouse.A data science team wants to use Amazon Redshift machine learning (Amazon Redshift ML) to build a model and run predictions for new data directly within the data warehouse.Which combination of steps should the company take to use Amazon Redshift ML to meet these requirements? (Choose three.)Read More →

A Data Scientist needs to analyze employment data.The dataset contains approximately 10 million observations on people across 10 different features.During the preliminary analysis, the Data Scientist notices that income and age distributions are not normal.While income levels shows a right skew as expected, with fewer individuals having a higher income, the age distribution also shows a right skew, with fewer older individuals participating in the workforce.Which feature transformations can the Data Scientist apply to fix the incorrectly skewed data? (Choose two.)Read More →

A Machine Learning Specialist needs to move and transform data in preparation for training.Some of the data needs to be processed in near-real time, and other data can be moved hourly.There are existing Amazon EMR MapReduce jobs to clean and feature engineering to perform on the data.Which of the following services can feed data to the MapReduce jobs? (Choose two.)Read More →

A Data Scientist wants to gain real-time insights into a data stream of GZIP files.Which solution would allow the use of SQL to query the stream with the LEAST latency?Read More →

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?Read More →

A data scientist has developed a machine learning translation model for English to Japanese by using Amazon SageMaker’s built-in seq2seq algorithm with500,000 aligned sentence pairs.While testing with sample sentences, the data scientist finds that the translation quality is reasonable for an example as short as five words.However, the quality becomes unacceptable if the sentence is 100 words long.Which action will resolve the problem?Read More →

A Machine Learning Specialist is configuring Amazon SageMaker so multiple Data Scientists can access notebooks, train models, and deploy endpoints.To ensure the best operational performance, the Specialist needs to be able to track how often the Scientists are deploying models, GPU and CPU utilization on the deployed SageMaker endpoints, and all errors that are generated when an endpoint is invoked.Which services are integrated with Amazon SageMaker to track this information? (Choose two.)Read More →

A company hosts a machine learning (ML) dataset repository on Amazon S3.A data scientist is preparing the repository to train a model.The data scientist needs to redact personally identifiable information (PH) from the dataset.Which solution will meet these requirements with the LEAST development effort?Read More →