Free Practice Amazon MLS-C01 Exam Questions 2025

Stay ahead with 100% Free AWS Certified Machine Learning - Specialty MLS-C01 Dumps Practice Questions

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Total 385 Questions | Updated On: Feb 19, 2025

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Question 1

An online reseller has a large, multi-column dataset with one column missing 30% of its data A Machine Learning Specialist believes that certain columns in the dataset could be used to reconstruct the missing data.

Which reconstruction approach should the Specialist use to preserve the integrity of the dataset?

A : Listwise deletion

B : Last observation carried forward

C : Multiple imputation

D : Mean substitution

Answer: C

Question 2

A company wants to create an artificial intelligence (AШ) yoga instructor that can lead large classes of students. The company needs to create a feature that can accurately count the number of students who are in a class. The company also needs a feature that can differentiate students who are performing a yoga stretch correctly from students who are performing a stretch incorrectly.

Determine whether students are performing a stretch correctly, the solution needs to measure the location and angle of each student’s arms and legs. A data scientist must use Amazon SageMaker to access video footage of a yoga class by extracting image frames and applying computer vision models.

Which combination of models will meet these requirements with the LEAST effort? (Choose two.)

A : Image Classification

B : Optical Character Recognition (OCR)

C : Object Detection

D : Pose estimation

E : Image Generative Adversarial Networks (GANs)

Answer: A,E

Question 3

Amazon Connect has recently been tolled out across a company as a contact call center The solution has been configured to store voice call recordings on Amazon S3

The content of the voice calls are being analyzed for the incidents being discussed by the call operators Amazon Transcribe is being used to convert the audio to text, and the output is stored on Amazon S3

Which approach will provide the information required for further analysis?

A : Use Amazon Comprehend with the transcribed files to build the key topics

B : Use Amazon Translate with the transcribed files to train and build a model for the key topics

C : Use the AWS Deep Learning AMI with Gluon Semantic Segmentation on the transcribed files to train and build a model for the key topics

D : Use the Amazon SageMaker k-Nearest-Neighbors (kNN) algorithm on the transcribed files to generate a word embeddings dictionary for the key topics

Answer: B

Question 4

A manufacturing company has a large set of labeled historical sales data The manufacturer would like to predict how many units of a particular part should be produced each quarter Which machine learning approach should be used to solve this problem?

A : Logistic regression

B : Random Cut Forest (RCF)

C : Principal component analysis (PCA)

D : Linear regression

Answer: D

Question 5

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.)

A : Add more deep trees to the random forest to enable the model to learn more features.

B : indicate a copy of the samples in the test database in the training dataset

C : Generate more positive samples by duplicating the positive samples and adding a small amount of noise to the duplicated data.

D : Change the cost function so that false negatives have a higher impact on the cost value than false positives

E : Change the cost function so that false positives have a higher impact on the cost value than false negatives

Answer: C,D

Page: 1 / 77

Total 385 Questions | Updated On: Feb 19, 2025

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