Exam Name: | AWS Certified Machine Learning - Specialty | ||
Exam Code: | MLS-C01 Dumps | ||
Vendor: | Amazon Web Services | Certification: | AWS Certified Specialty |
Questions: | 281 Q&A's | Shared By: | rueben |
A company has raw user and transaction data stored in AmazonS3 a MySQL database, and Amazon RedShift A Data Scientist needs to perform an analysis by joining the three datasets from Amazon S3, MySQL, and Amazon RedShift, and then calculating the average-of a few selected columns from the joined data
Which AWS service should the Data Scientist use?
A data scientist receives a collection of insurance claim records. Each record includes a claim ID. the final outcome of the insurance claim, and the date of the final outcome.
The final outcome of each claim is a selection from among 200 outcome categories. Some claim records include only partial information. However, incomplete claim records include only 3 or 4 outcome ...gones from among the 200 available outcome categories. The collection includes hundreds of records for each outcome category. The records are from the previous 3 years.
The data scientist must create a solution to predict the number of claims that will be in each outcome category every month, several months in advance.
Which solution will meet these requirements?
A machine learning specialist needs to analyze comments on a news website with users across the globe. The specialist must find the most discussed topics in the comments that are in either English or Spanish.
What steps could be used to accomplish this task? (Choose two.)
A medical device company is building a machine learning (ML) model to predict the likelihood of device recall based on customer data that the company collects from a plain text survey. One of the survey questions asks which medications the customer is taking. The data for this field contains the names of medications that customers enter manually. Customers misspell some of the medication names. The column that contains the medication name data gives a categorical feature with high cardinality but redundancy.
What is the MOST effective way to encode this categorical feature into a numeric feature?