Free Amazon MLS-C01 Exam Questions

Become Amazon Certified with updated MLS-C01 exam questions and correct answers

Page:    1 / 79      
Total 392 Questions | Updated On: Apr 01, 2026
Add To Cart
Question 1

A company has a podcast platform that has thousands of users. The company has implemented an anomaly detection algorithm to detect low podcast engagement based on a 10-minute running window of user events such as listening, pausing, and exiting the podcast. A machine learning (ML) specialist is designing the data ingestion of these events with the knowledge that the event payload needs some small transformations before inference. How should the ML specialist design the data ingestion to meet these requirements with the LEAST operational overhead?


Answer: B
Question 2

A credit card company wants to build a credit scoring model to help predict whether a new credit card applicant
will default on a credit card payment. The company has collected data from a large number of sources with
thousands of raw attributes. Early experiments to train a classification model revealed that many attributes are
highly correlated, the large number of features slows down the training speed significantly, and that there are
some overfitting issues.
The Data Scientist on this project would like to speed up the model training time without losing a lot of
information from the original dataset.
Which feature engineering technique should the Data Scientist use to meet the objectives?


Answer: B
Question 3

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?


Answer: D
Question 4

A gaming company has launched an online game where people can start playing for free but they need to pay if they choose to use certain features The company needs to build an automated system to predict whether or not a new user will become a paid user within 1 year The company has gathered a labeled dataset from 1 million users
The training dataset consists of 1.000 positive samples (from users who ended up paying within 1 year) and 999.000 negative samples (from users who did not use any paid features) Each data sample consists of 200 features including user age, device, location, and play patterns
Using this dataset for training, the Data Science team trained a random forest model that converged with over 99?curacy on the training set However, the prediction results on a test dataset were not satisfactory.
Which of the following approaches should the Data Science team take to mitigate this issue? (Select TWO.)


Answer: C,D
Question 5

A large consumer goods manufacturer has the following products on sale
* 34 different toothpaste variants
* 48 different toothbrush variants
* 43 different mouthwash variants
The entire sales history of all these products is available in Amazon S3 Currently, the company is using custom-built autoregressive integrated moving average (ARIMA) models to forecast demand for these products The company wants to predict the demand for a new product that will soon be launched
Which solution should a Machine Learning Specialist apply?


Answer: B
Page:    1 / 79      
Total 392 Questions | Updated On: Apr 01, 2026
Add To Cart

© Copyrights DumpsCertify 2026. All Rights Reserved

We use cookies to ensure your best experience. So we hope you are happy to receive all cookies on the DumpsCertify.