Free AWS MLS-C01 Practice Questions & Answers 2026 Part2

Question #1

A Machine Learning Specialist has created a deep learning neural network model that performs well on the training data but performs poorly on the test data.Which of the following methods should the Specialist consider using to correct this? (Choose three.)

A. Decrease regularization

B. Increase regularization

C. Increase dropout

D. Decrease dropout

E. Increase feature combinations

F. Decrease feature combinations

View answer

Correct Answer: BCF

Question #2

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

View answer

Correct Answer: C

Question #3

[Modeling]A data scientist is working on a public sector project for an urban traffic system. While studying the traffic patterns, it is clear to the data scientist that the traffic behavior at each light is correlated, subject to a small stochastic error term. The data scientist must model the traffic behavior to analyze the traffic patterns and reduce congestion.How will the data scientist MOST effectively model the problem?

A. The data scientist should obtain a correlated equilibrium policy by formulating this problem as a multi-agent reinforcement learning problem

B. The data scientist should obtain the optimal equilibrium policy by formulating this problem as a single-agent reinforcement learning problem

C. Rather than finding an equilibrium policy, the data scientist should obtain accurate predictors of traffic flow by using historical data through a supervised learning approach

D. Rather than finding an equilibrium policy, the data scientist should obtain accurate predictors of traffic flow by using unlabeled simulated data representing the new traffic patterns in the city and applying an unsupervised learning approach

View answer

Correct Answer: A

Question #4

A Machine Learning Specialist is packaging a custom ResNet model into a Docker container so the company can leverage Amazon SageMaker for training. The Specialist is using Amazon EC2 P3 instances to train the model and needs to properly configure the Docker container to leverage the NVIDIA GPUs.What does the Specialist need to do?

A. Bundle the NVIDIA drivers with the Docker image

B. Build the Docker container to be NVIDIA-Docker compatible

C. Organize the Docker container's file structure to execute on GPU instances

D. Set the GPU flag in the Amazon SageMaker CreateTrainingJob request body

View answer

Correct Answer: B

Question #5

A company is using Amazon Textract to extract textual data from thousands of scanned text-heavy legal documents daily. The company uses this information to process loan applications automatically. Some of the documents fail business validation and are returned to human reviewers, who investigate the errors. This activity increases the time to process the loan applications.What should the company do to reduce the processing time of loan applications?

A. onfigure Amazon Textract to route low-confidence predictions to Amazon SageMaker Ground Truth

B. se an Amazon Textract synchronous operation instead of an asynchronous operation

C. onfigure Amazon Textract to route low-confidence predictions to Amazon Augmented AI (Amazon A2I)

D. se Amazon Rekognition's feature to detect text in an image to extract the data from scanned images

View answer

Correct Answer: C

Question #6

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

View answer

Correct Answer: C

Question #7

A Machine Learning Specialist at a company sensitive to security is preparing a dataset for model training. The dataset is stored in Amazon S3 and contains Personally Identifiable Information (PII).The dataset:•Must be accessible from a VPC only.•Must not traverse the public internet.How can these requirements be satisfied?

A. Create a VPC endpoint and apply a bucket access policy that restricts access to the given VPC endpoint and the VPC

B. Create a VPC endpoint and apply a bucket access policy that allows access from the given VPC endpoint and an Amazon EC2 instance

C. Create a VPC endpoint and use Network Access Control Lists (NACLs) to allow traffic between only the given VPC endpoint and an Amazon EC2 instance

D. Create a VPC endpoint and use security groups to restrict access to the given VPC endpoint and an Amazon EC2 instance

View answer

Correct Answer: A

Question #8

A company is setting up an Amazon SageMaker environment. The corporate data security policy does not allow communication over the internet.How can the company enable the Amazon SageMaker service without enabling direct internet access to Amazon SageMaker notebook instances?

A. Create a NAT gateway within the corporate VPC

B. Route Amazon SageMaker traffic through an on-premises network

C. Create Amazon SageMaker VPC interface endpoints within the corporate VP

D. Create VPC peering with Amazon VPC hosting Amazon SageMaker

View answer

Correct Answer: C

Question #9

A Machine Learning Specialist is developing a custom video recommendation model for an application. The dataset used to train this model is very large withmillions of data points and is hosted in an Amazon S3 bucket. The Specialist wants to avoid loading all of this data onto an Amazon SageMaker notebook instancebecause it would take hours to move and will exceed the attached 5 GB Amazon EBS volume on the notebook instance.Which approach allows the Specialist to use all the data to train the model?

A. Load a smaller subset of the data into the SageMaker notebook and train locally

B. Launch an Amazon EC2 instance with an AWS Deep Learning AMI and attach the S3 bucket to the instance

C. Use AWS Glue to train a model using a small subset of the data to confirm that the data will be compatible with Amazon SageMaker

D. Load a smaller subset of the data into the SageMaker notebook and train locally

View answer

Correct Answer: A

Question #10

A Marketing Manager at a pet insurance company plans to launch a targeted marketing campaign on social media to acquire new customers. Currently, the company has the following data in Amazon Aurora:•Profiles for all past and existing customers•Profiles for all past and existing insured pets•Policy-level information•Premiums received•Claims paidWhat steps should be taken to implement a machine learning model to identify potential new customers on social media?

A. Use regression on customer profile data to understand key characteristics of consumer segments

B. Use clustering on customer profile data to understand key characteristics of consumer segments

C. Use a recommendation engine on customer profile data to understand key characteristics of consumer segments

D. Use a decision tree classifier engine on customer profile data to understand key characteristics of consumer segments

View answer

Correct Answer: C

Question #11

A company is using Amazon Polly to translate plaintext documents to speech for automated company announcements. However, company acronyms are being mispronounced in the current documents.How should a Machine Learning Specialist address this issue for future documents?

A. Convert current documents to SSML with pronunciation tags

B. Create an appropriate pronunciation lexicon

C. Output speech marks to guide in pronunciation

D. Use Amazon Lex to preprocess the text files for pronunciation

View answer

Correct Answer: A

Question #12

A Machine Learning Specialist is creating a new natural language processing application that processes a dataset comprised of 1 million sentences. The aim is to then run Word2Vec to generate embeddings of the sentences and enable different types of predictions.Here is an example from the dataset:"The quck BROWN FOX jumps over the lazy dog.”Which of the following are the operations the Specialist needs to perform to correctly sanitize and prepare the data in a repeatable manner? (Choose three.)

A. Perform part-of-speech tagging and keep the action verb and the nouns only

B. Normalize all words by making the sentence lowercase

C. Remove stop words using an English stopword dictionary

D. Correct the typography on "quck" to "quick

E. One-hot encode all words in the sentence

F. Tokenize the sentence into words

View answer

Correct Answer: BCF

Question #13

A manufacturing company has structured and unstructured data stored in an Amazon S3 bucket. A Machine Learning Specialist wants to use SQL to run queries on this data.Which solution requires the LEAST effort to be able to query this data?

A. Use AWS Data Pipeline to transform the data and Amazon RDS to run queries

B. Use AWS Glue to catalogue the data and Amazon Athena to run queries

C. Use AWS Batch to run ETL on the data and Amazon Aurora to run the queries

D. Use AWS Lambda to transform the data and Amazon Kinesis Data Analytics to run queries

View answer

Correct Answer: B

Question #14

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

View answer

Correct Answer: C

Question #15

A data science team is planning to build a natural language processing (NLP) application. The application's text preprocessing stage will include part-of-speech tagging and key phase extraction. The preprocessed text will be input to a custom classification algorithm that the data science team has already written and trained using Apache MXNet.Which solution can the team build MOST quickly to meet these requirements?

A. se an NLP library in Amazon SageMaker for the part-of-speech tagging

B. se Amazon Comprehend for the part-of-speech tagging, key phase extraction, and classification tasks

C. se Amazon Comprehend for the part-of-speech tagging and key phase extraction tasks

D. se Amazon Comprehend for the part-of-speech tagging and key phase extraction tasks

View answer

Correct Answer: D

Question #16

A Machine Learning Specialist built an image classification deep learning model. However, the Specialist ran into an overfitting problem in which the training and testing accuracies were 99% and 75%, respectively.How should the Specialist address this issue and what is the reason behind it?

A. he learning rate should be increased because the optimization process was trapped at a local minimum

B. he dropout rate at the flatten layer should be increased because the model is not generalized enough

C. he dimensionality of dense layer next to the flatten layer should be increased because the model is not complex enough

D. he epoch number should be increased because the optimization process was terminated before it reached the global minimum

View answer

Correct Answer: B

Question #17

A company is setting up an Amazon SageMaker environment. The corporate data security policy does not allow communication over the internet.How can the company enable the Amazon SageMaker service without enabling direct internet access to Amazon SageMaker notebook instances?

A. Create a NAT gateway within the corporate VPC

B. Route Amazon SageMaker traffic through an on-premises network

C. Create Amazon SageMaker VPC interface endpoints within the corporate VP

D. Create VPC peering with Amazon VPC hosting Amazon SageMaker

View answer

Correct Answer: C

Question #18

A company wants to use automatic speech recognition (ASR) to transcribe messages that are less than 60 seconds long from a voicemail-style application. The company requires the correct identification of 200 unique product names, some of which have unique spellings or pronunciations.

A. Use a voice-driven Amazon Lex bot to perform the ASR customization

B. Use Amazon Transcribe to perform the ASR customization

C. Create a custom vocabulary file containing each product name with phonetic pronunciations, and use it with Amazon Transcribe to perform the ASR customization

D. Use the audio transcripts to create a training dataset and build an Amazon Transcribe custom language model

View answer

Correct Answer: C

Question #19

A company is setting up an Amazon SageMaker environment. The corporate data security policy does not allow communication over the internet.How can the company enable the Amazon SageMaker service without enabling direct internet access to Amazon SageMaker notebook instances?

A. Create a NAT gateway within the corporate VPC

B. Route Amazon SageMaker traffic through an on-premises network

C. Create Amazon SageMaker VPC interface endpoints within the corporate VP

D. Create VPC peering with Amazon VPC hosting Amazon SageMaker

View answer

Correct Answer: C

Question #20

A Machine Learning Specialist is building a convolutional neural network (CNN) that will classify 10 types of animals. The Specialist has built a series of layers in a neural network that will take an input image of an animal, pass it through a series of convolutional and pooling layers, and then finally pass it through a dense and fully connected layer with 10 nodes. The Specialist would like to get an output from the neural network that is a probability distribution of how likely it is that the input image belongs to each of the 10 classes.Which function will produce the desired output?

A. Dropout

B. Smooth L1 loss

C. Softmax

D. Rectified linear units (ReLU)

View answer

Correct Answer: C

Question #21

A Machine Learning Specialist is training a model to identify the make and model of vehicles in images. The Specialist wants to use transfer learning and an existing model trained on images of general objects. The Specialist collated a large custom dataset of pictures containing different vehicle makes and models.What should the Specialist do to initialize the model to re-train it with the custom data?

A. Initialize the model with random weights in all layers including the last fully connected layer

B. Initialize the model with pre-trained weights in all layers and replace the last fully connected layer

C. Initialize the model with random weights in all layers and replace the last fully connected layer

D. Initialize the model with pre-trained weights in all layers including the last fully connected layer

View answer

Correct Answer: B

Question #22

A Data Science team is designing a dataset repository where it will store a large amount of training data commonly used in its machine learning models. As Data Scientists may create an arbitrary number of new datasets every day, the solution has to scale automatically and be cost-effective. Also, it must be possible to explore the data using SQL.Which storage scheme is MOST adapted to this scenario?

A. Store datasets as files in Amazon S3

B. Store datasets as files in an Amazon EBS volume attached to an Amazon EC2 instance

C. Store datasets as tables in a multi-node Amazon Redshift cluster

D. Store datasets as global tables in Amazon DynamoDB

View answer

Correct Answer: A

Question #23

A Machine Learning Specialist is working for a credit card processing company and receives an unbalanced dataset containing credit card transactions. It contains 99,000 valid transactions and 1,000 fraudulent transactions The Specialist is asked to score a model that was run against the dataset The Specialist has been advised that identifying valid transactions is equally as important as identifying fraudulent transactions What metric is BEST suited to score the model?

A. Precision

B. Recall

C. Area Under the ROC Curve (AUC)

D. Root Mean Square Error (RMSE)

View answer

Correct Answer: A

Question #24

An office security agency conducted a successful pilot using 100 cameras installed at key locations within the main office. Images from the cameras were uploaded to Amazon S3 and tagged using Amazon Rekognition, and the results were stored in Amazon ES. The agency is now looking to expand the pilot into a full production system using thousands of video cameras in its office locations globally. The goal is to identify activities performed by non-employees in real timeWhich solution should the agency consider?

A. Use a proxy server at each local office and for each camera, and stream the RTSP feed to a unique Amazon Kinesis Video Streams video stream

B. Use a proxy server at each local office and for each camera, and stream the RTSP feed to a unique Amazon Kinesis Video Streams video stream

C. Install AWS DeepLens cameras and use the DeepLens_Kinesis_Video module to stream video to Amazon Kinesis Video Streams for each camera

D. Install AWS DeepLens cameras and use the DeepLens_Kinesis_Video module to stream video to Amazon Kinesis Video Streams for each camera

View answer

Correct Answer: A

Question #25

A Machine Learning Specialist is training a model to identify the make and model of vehicles in images. The Specialist wants to use transfer learning and an existing model trained on images of general objects. The Specialist collated a large custom dataset of pictures containing different vehicle makes and models.What should the Specialist do to initialize the model to re-train it with the custom data?

A. Initialize the model with random weights in all layers including the last fully connected layer

B. Initialize the model with pre-trained weights in all layers and replace the last fully connected layer

C. Initialize the model with random weights in all layers and replace the last fully connected layer

D. Initialize the model with pre-trained weights in all layers including the last fully connected layer

View answer

Correct Answer: B

Question #26

A company is using Amazon Polly to translate plaintext documents to speech for automated company announcements. However, company acronyms are being mispronounced in the current documents.How should a Machine Learning Specialist address this issue for future documents?

A. Convert current documents to SSML with pronunciation tags

B. Create an appropriate pronunciation lexicon

C. Output speech marks to guide in pronunciation

D. Use Amazon Lex to preprocess the text files for pronunciation

View answer

Correct Answer: A

Question #27

A Machine Learning Specialist deployed a model that provides product recommendations on a company's website. Initially, the model was performing very well and resulted in customers buying more products on average. However, within the past few months, the Specialist has noticed that the effect of product recommendations has diminished and customers are starting to return to their original habits of spending less. The Specialist is unsure of what happened, as the model has not changed from its initial deployment over a year ago.Which method should the Specialist try to improve model performance?

A. The model needs to be completely re-engineered because it is unable to handle product inventory changes

B. The model's hyperparameters should be periodically updated to prevent drift

C. The model should be periodically retrained from scratch using the original data while adding a regularization term to handle product inventory changes

D. The model should be periodically retrained using the original training data plus new data as product inventory changes

View answer

Correct Answer: D

Question #28

[Modeling] A data scientist must build a custom recommendation model in Amazon SageMaker for an online retail company. Due to the nature of the company's products, customers buy only 4-5 products every 5-10 years. So, the company relies on a steady stream of new customers. When a new customer signs up, the company collects data on the customer's preferences. Below is a sample of the data available to the data scientist. How should the data scientist split the dataset into a training and test set for this use case?

A. Shuffle all interaction data

B. Identify the most recent 10% of interactions for each user

C. Identify the 10% of users with the least interaction data

D. Randomly select 10% of the users

View answer

Correct Answer: D

Question #29

A Marketing Manager at a pet insurance company plans to launch a targeted marketing campaign on social media to acquire new customers. Currently, the company has the following data in Amazon Aurora:•Profiles for all past and existing customers•Profiles for all past and existing insured pets•Policy-level information•Premiums received•Claims paidWhat steps should be taken to implement a machine learning model to identify potential new customers on social media?

A. Use regression on customer profile data to understand key characteristics of consumer segments

B. Use clustering on customer profile data to understand key characteristics of consumer segments

C. Use a recommendation engine on customer profile data to understand key characteristics of consumer segments

D. Use a decision tree classifier engine on customer profile data to understand key characteristics of consumer segments

View answer

Correct Answer: C

Question #30

Machine Learning Specialist is working with a media company to perform classification on popular articles from the company's website. The company is using random forests to classify how popular an article will be before it is published. A sample of the data being used is below.Given the dataset, the Specialist wants to convert the Day_Of_Week column to binary values.What technique should be used to convert this column to binary values?

A. Binarization

B. One-hot encoding

C. Tokenization

D. Normalization transformation

View answer

Correct Answer: B

Question #31

A company wants to classify user behavior as either fraudulent or normal. Based on internal research, a Machine Learning Specialist would like to build a binary classifier based on two features: age of account and transaction month. The class distribution for these features is illustrated in the figure provided.Based on this information, which model would have the HIGHEST accuracy?

A. Long short-term memory (LSTM) model with scaled exponential linear unit (SELU)

B. Logistic regression

C. Support vector machine (SVM) with non-linear kernel

D. Single perceptron with tanh activation function

View answer

Correct Answer: C

Question #32

A Machine Learning Specialist has created a deep learning neural network model that performs well on the training data but performs poorly on the test data.Which of the following methods should the Specialist consider using to correct this? (Choose three.)

A. ecrease regularization

B. ncrease regularization

C. ncrease dropout

D. ecrease dropout

E. ncrease feature combinations

F. ecrease feature combinations

View answer

Correct Answer: BCF

Question #33

A machine learning (ML) engineer is creating a binary classification model. The ML engineer will use the model in a highly sensitive environment.

A. Accuracy

B. Precision

C. Recall

D. F1

View answer

Correct Answer: B

Question #34

A Machine Learning Specialist is building a logistic regression model that will predict whether or not a person will order a pizza. The Specialist is trying to build the optimal model with an ideal classification threshold.What model evaluation technique should the Specialist use to understand how different classification thresholds will impact the model's performance?

A. Receiver operating characteristic (ROC) curve

B. Misclassification rate

C. Root Mean Square Error (RMSE)

D. L1 norm

View answer

Correct Answer: A

Question #35

A Marketing Manager at a pet insurance company plans to launch a targeted marketing campaign on social media to acquire new customers. Currently, the company has the following data in Amazon Aurora:•Profiles for all past and existing customers•Profiles for all past and existing insured pets•Policy-level information•Premiums received•Claims paidWhat steps should be taken to implement a machine learning model to identify potential new customers on social media?

A. Use regression on customer profile data to understand key characteristics of consumer segments

B. Use clustering on customer profile data to understand key characteristics of consumer segments

C. Use a recommendation engine on customer profile data to understand key characteristics of consumer segments

D. Use a decision tree classifier engine on customer profile data to understand key characteristics of consumer segments

View answer

Correct Answer: C

Question #36

An office security agency conducted a successful pilot using 100 cameras installed at key locations within the main office. Images from the cameras were uploaded to Amazon S3 and tagged using Amazon Rekognition, and the results were stored in Amazon ES. The agency is now looking to expand the pilot into a full production system using thousands of video cameras in its office locations globally. The goal is to identify activities performed by non-employees in real timeWhich solution should the agency consider?

A. Use a proxy server at each local office and for each camera, and stream the RTSP feed to a unique Amazon Kinesis Video Streams video stream

B. Use a proxy server at each local office and for each camera, and stream the RTSP feed to a unique Amazon Kinesis Video Streams video stream

C. Install AWS DeepLens cameras and use the DeepLens_Kinesis_Video module to stream video to Amazon Kinesis Video Streams for each camera

D. Install AWS DeepLens cameras and use the DeepLens_Kinesis_Video module to stream video to Amazon Kinesis Video Streams for each camera

View answer

Correct Answer: A

Question #37

When submitting Amazon SageMaker training jobs using one of the built-in algorithms, which common parameters MUST be specified? (Choose three.)

A. The training channel identifying the location of training data on an Amazon S3 bucket

B. The validation channel identifying the location of validation data on an Amazon S3 bucket

C. The IAM role that Amazon SageMaker can assume to perform tasks on behalf of the users

D. Hyperparameters in a JSON array as documented for the algorithm used

E. The Amazon EC2 instance class specifying whether training will be run using CPU or GPU

F. The output path specifying where on an Amazon S3 bucket the trained model will persist

View answer

Correct Answer: AEF

Question #38

A Machine Learning Specialist working for an online fashion company wants to build a data ingestion solution for the company's Amazon S3-based data lake.The Specialist wants to create a set of ingestion mechanisms that will enable future capabilities comprised of:✑ Real-time analytics✑ Interactive analytics of historical data✑ Clickstream analytics✑ Product recommendationsWhich services should the Specialist use?

A. WS Glue as the data catalog; Amazon Kinesis Data Streams and Amazon Kinesis Data Analytics for real-time data insights; Amazon Kinesis Data Firehose for delivery to Amazon ES for clickstream analytics; Amazon EMR to generate personalized product recommendations

B. mazon Athena as the data catalog: Amazon Kinesis Data Streams and Amazon Kinesis Data Analytics for near-real-time data insights; Amazon Kinesis Data Firehose for clickstream analytics; AWS Glue to generate personalized product recommendations

C. WS Glue as the data catalog; Amazon Kinesis Data Streams and Amazon Kinesis Data Analytics for historical data insights; Amazon Kinesis Data Firehose for delivery to Amazon ES for clickstream analytics; Amazon EMR to generate personalized product recommendations

D. mazon Athena as the data catalog; Amazon Kinesis Data Streams and Amazon Kinesis Data Analytics for historical data insights; Amazon DynamoDB streams for clickstream analytics; AWS Glue to generate personalized product recommendations

View answer

Correct Answer: A

Question #39

A Machine Learning Specialist is designing a system for improving sales for a company. The objective is to use the large amount of information the company has on users’ behavior and product preferences to predict which products users would like based on the users’ similarity to other users.What should the Specialist do to meet this objective?

A. Build a content-based filtering recommendation engine with Apache Spark ML on Amazon EMR

B. Build a collaborative filtering recommendation engine with Apache Spark ML on Amazon EMR

C. Build a model-based filtering recommendation engine with Apache Spark ML on Amazon EMR

D. Build a combinative filtering recommendation engine with Apache Spark ML on Amazon EMR

View answer

Correct Answer: B

Question #40

A large mobile network operating company is building a machine learning model to predict customers who are likely to unsubscribe from the service. The company plans to offer an incentive for these customers as the cost of churn is far greater than the cost of the incentive.The model produces the following confusion matrix after evaluating on a test dataset of 100 customers:Based on the model evaluation results, why is this a viable model for production?

A. The model is 86% accurate and the cost incurred by the company as a result of false negatives is less than the false positives

B. The precision of the model is 86%, which is less than the accuracy of the model

C. The model is 86% accurate and the cost incurred by the company as a result of false positives is less than the false negatives

D. The precision of the model is 86%, which is greater than the accuracy of the model

View answer

Correct Answer: A

Question #41

A Data Scientist needs to create a serverless ingestion and analytics solution for high-velocity, real-time streaming data.The ingestion process must buffer and convert incoming records from JSON to a query-optimized, columnar format without data loss. The output datastore must be highly available, and Analysts must be able to run SQL queries against the data and connect to existing business intelligence dashboards.Which solution should the Data Scientist build to satisfy the requirements?

A. reate a schema in the AWS Glue Data Catalog of the incoming data format

B. rite each JSON record to a staging location in Amazon S3

C. rite each JSON record to a staging location in Amazon S3

D. se Amazon Kinesis Data Analytics to ingest the streaming data and perform real-time SQL queries to convert the records to Apache Parquet before delivering to Amazon S3

View answer

Correct Answer: A

Question #42

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

View answer

Correct Answer: C

Question #43

A company wants to classify user behavior as either fraudulent or normal. Based on internal research, a Machine Learning Specialist would like to build a binary classifier based on two features: age of account and transaction month. The class distribution for these features is illustrated in the figure provided.Based on this information, which model would have the HIGHEST recall with respect to the fraudulent class?

A. Decision tree

B. Linear support vector machine (SVM)

C. Naive Bayesian classifier

D. Single Perceptron with sigmoidal activation function

View answer

Correct Answer: C

Question #44

A monitoring service generates 1 TB of scale metrics record data every minute. A Research team performs queries on this data using Amazon Athena. The queries run slowly due to the large volume of data, and the team requires better performance.How should the records be stored in Amazon S3 to improve query performance?

A. CSV files

B. Parquet files

C. Compressed JSON

D. RecordIO

View answer

Correct Answer: B

Question #45

A Machine Learning Specialist is training a model to identify the make and model of vehicles in images. The Specialist wants to use transfer learning and an existing model trained on images of general objects. The Specialist collated a large custom dataset of pictures containing different vehicle makes and models.What should the Specialist do to initialize the model to re-train it with the custom data?

A. Initialize the model with random weights in all layers including the last fully connected layer

B. Initialize the model with pre-trained weights in all layers and replace the last fully connected layer

C. Initialize the model with random weights in all layers and replace the last fully connected layer

D. Initialize the model with pre-trained weights in all layers including the last fully connected layer

View answer

Correct Answer: B

Question #46

[Exploratory Data Analysis] A machine learning (ML) engineer is preparing a dataset for a classification model. The ML engineer notices that some continuous numeric features have a significantly greater value than most other features. A business expert explains that the features are independently informative and that the dataset is representative of the target distribution. After training, the model's inferences accuracy is lower than expected. Which preprocessing technique will result in the GREATEST increase of the model's inference accuracy?

A. Normalize the problematic features

B. Bootstrap the problematic features

C. Remove the problematic features

D. Extrapolate synthetic features

View answer

Correct Answer: A

Question #47

A Data Science team is designing a dataset repository where it will store a large amount of training data commonly used in its machine learning models. As Data Scientists may create an arbitrary number of new datasets every day, the solution has to scale automatically and be cost-effective. Also, it must be possible to explore the data using SQL.Which storage scheme is MOST adapted to this scenario?

A. Store datasets as files in Amazon S3

B. Store datasets as files in an Amazon EBS volume attached to an Amazon EC2 instance

C. Store datasets as tables in a multi-node Amazon Redshift cluster

D. Store datasets as global tables in Amazon DynamoDB

View answer

Correct Answer: A

Question #48

A monitoring service generates 1 TB of scale metrics record data every minute. A Research team performs queries on this data using Amazon Athena. The queries run slowly due to the large volume of data, and the team requires better performance.How should the records be stored in Amazon S3 to improve query performance?

A. CSV files

B. Parquet files

C. Compressed JSON

D. RecordIO

View answer

Correct Answer: B

Question #49

A city wants to monitor its air quality to address the consequences of air pollution. A Machine Learning Specialist needs to forecast the air quality in parts per million of contaminates for the next 2 days in the city. As this is a prototype, only daily data from the last year is available.Which model is MOST likely to provide the best results in Amazon SageMaker?

A. Use the Amazon SageMaker k-Nearest-Neighbors (kNN) algorithm on the single time series consisting of the full year of data with a predictor_type of regressor

B. Use Amazon SageMaker Random Cut Forest (RCF) on the single time series consisting of the full year of data

C. Use the Amazon SageMaker Linear Learner algorithm on the single time series consisting of the full year of data with a predictor_type of regressor

D. Use the Amazon SageMaker Linear Learner algorithm on the single time series consisting of the full year of data with a predictor_type of classifier

View answer

Correct Answer: C

Question #50

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

View answer

Correct Answer: C

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