Amazon MLA-C01 DUMPS WITH REAL EXAM QUESTIONS

PDF Last Updated : Dec 01, 2024
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Free Amazon MLA-C01 Sample Questions

Question 1

A college endowment office is using S3 data lake with structured and unstructured data to identify potential big donors. Many different data lake records refer to the same person, so fundraisers need to de-duplicate data before storing it and preparing for further processing. What is the easiest and most effective way to achieve that goal?

A Write a Python code for a custom de-duplication and run it on EMR cluster.
B Use AWS Glue Crawler to identify and eliminate duplicate people.
C Find a matching algorithm on AMI Marketplace.
D Store data in compressed JSON format. 

Answer: B

Question 2

A Machine Learning Engineer is tasked with developing a server less BI Dashboard on AWS that has ML methods build-in. What is the best AWS service he can choose?

A Google BI integrated with AWS Dash
B AWS Quick Sight
C AWS Tableau
D  Sage Maker Server less

Answer: B

Question 3

Mark is running a small print-on-demand (POD) business. This month he has been selling an average of 5 T-shirts per day. He is running low on inventory and he wants to calculate the probability that he will sell more than 10 T-shirts tomorrow. What probability distribution should he use for that calculation?

A Poisson distribution
B Normal (Gaussian) distribution
C Modified alpha distribution
D Student t-distribution

Answer: A

Question 4

The AWS Glue Data Catalog contains references to data that are used as sources and targets of extract, transform, and load (ETL) jobs in AWS Glue. To create a data warehouse or data lake, a user must catalog this data. One way to take inventory of the data in the data store is to run a Glue crawler. What is NOT the datastore a crawler can connect to?

A Amazon S3
B Amazon Redshift
C JDBC API
D Amazon Elasti Cache

Answer: D

Question 5

A Data Scientist is dealing with s binary classification problem with highly imbalanced classes in a 1:200 ratio. He wants to fit and evaluate a decision tree algorithm but does not expect it to perform very well on a raw unbalanced dataset. What are the two techniques he can use as data preparation? (Select TWO.)

A Transform Training Data with SMOTE
B Under-sample majority (normal) class.
C Use SVM (Support-Vector Machine) Algorithm.
D Normalize features of the majority class.
E Collect more data.

Answer: A,B

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