MLS-C01 Exam Questions
388 real MLS-C01 exam questions with expert-verified answers and explanations. Page 5 of 8.
- Question #201Modeling
A global financial company is using machine learning to automate its loan approval process. The company has a dataset of customer information. The dataset contains some categorical...
Feature EngineeringData PreprocessingOverfittingCategorical Data Encoding - Question #202ML Implementation and Operations
A machine learning (ML) specialist needs to extract embedding vectors from a text series. The goal is to provide a ready-to-ingest feature space for a data scientist to develop dow...
Text embeddingsNatural Language ProcessingSageMaker algorithmsFeature engineering - Question #203Machine Learning Implementation and Operations
A retail company wants to update its customer support system. The company wants to implement automatic routing of customer claims to different queues to prioritize the claims by ca...
Text ClassificationAWS AI ServicesLow-code MLData Preparation - Question #204Modeling
A machine learning (ML) specialist is using Amazon SageMaker hyperparameter optimization (HPO) to improve a model's accuracy. The learning rate parameter is specified in the follow...
SageMaker HPOHyperparameter TuningModel OptimizationSearch Strategy - Question #205Machine Learning Implementation and Operations
A manufacturing company wants to use machine learning (ML) to automate quality control in its facilities. The facilities are in remote locations and have limited internet connectiv...
Amazon SageMakerAWS IoT GreengrassEdge MLML Workflow - Question #206Machine Learning Implementation and Operations
A company has an ecommerce website with a product recommendation engine built in TensorFlow. The recommendation engine endpoint is hosted by Amazon SageMaker. Three compute-optimiz...
SageMaker Auto ScalingElastic InferenceModel DeploymentCost Optimization - Question #207Modeling
A real-estate company is launching a new product that predicts the prices of new houses. The historical data for the properties and prices is stored in .csv format in an Amazon S3...
Amazon SageMakerModel ImprovementOperational EfficiencyFeature Engineering - Question #208Exploratory Data Analysis
A data scientist is reviewing customer comments about a company's products. The data scientist needs to present an initial exploratory analysis by using charts and a word cloud. Th...
Text PreprocessingFeature EngineeringNLP FundamentalsEDA Techniques - Question #209Modeling
A data scientist is evaluating a GluonTS on Amazon SageMaker DeepAR model. The evaluation metrics on the test set indicate that the coverage score is 0.489 and 0.889 at the 0.5 and...
Probabilistic ForecastingModel EvaluationCoverage ScoreModel Calibration - Question #210Data Engineering
An energy company has wind turbines, weather stations, and solar panels that generate telemetry data. The company wants to perform predictive maintenance on these devices. The devi...
AWS IoT CoreMQTTData IngestionIoT Data - Question #211Machine Learning Implementation and Operations
A retail company collects customer comments about its products from social media, the company website, and customer call logs. A team of data scientists and engineers wants to find...
Natural Language Processing (NLP)Text ClassificationAmazon ComprehendMulti-label Learning - Question #212Machine Learning Implementation and Operations
A data engineer is using AWS Glue to create optimized, secure datasets in Amazon S3. The data science team wants the ability to access the ETL scripts directly from Amazon SageMake...
AWS Glue Development EndpointAmazon SageMaker IntegrationIAM Roles and PoliciesAWS Networking (VPC) - Question #213ML Implementation and Operations
A Machine Learning Specialist is training a regression model to predict house prices in different locations. The Specialist wants to test the quality of the test data by identifyin...
Regression Model EvaluationResidual AnalysisModel DiagnosticsData Visualization - Question #214Data Engineering
A Machine Learning Specialist is preparing the dataset to be used for training a linear learner model in Amazon SageMaker. During exploratory data analysis, he has detected multipl...
Missing DataImputationData PreprocessingBias Reduction - Question #215Data Engineering
A company wants to conduct targeted marketing to sell solar panels to homeowners. The company wants to use machine learning (ML) technologies to identify which houses already have...
SageMaker Ground TruthData LabelingActive LearningWorkforce Management - Question #216Machine Learning Implementation and Operations
A machine learning (ML) specialist wants to bring a custom training algorithm to Amazon SageMaker. The ML specialist implements the algorithm in a Docker container that is supporte...
SageMaker Custom ContainersDockerfile ENTRYPOINTML Training EnvironmentContainer Packaging - Question #217Modeling
An ecommerce company wants to use machine learning (ML) to monitor fraudulent transactions on its website. The company is using Amazon SageMaker to research, train, deploy, and mon...
Anomaly DetectionUnsupervised LearningAmazon SageMaker Built-in AlgorithmsFraud Detection - Question #218Machine Learning Implementation and Operations
A healthcare company is using an Amazon SageMaker notebook instance to develop machine learning (ML) models. The company's data scientists will need to be able to access datasets s...
SageMaker NetworkingVPC EndpointsS3 Private AccessSecurity Best Practices - Question #219Modeling
A machine learning (ML) specialist at a retail company is forecasting sales for one of the company's stores. The ML specialist is using data from the past 10 years. The company has...
Time Series ForecastingSeasonalityFeature EngineeringModeling Techniques - Question #220Data Engineering
A data engineer needs to provide a team of data scientists with the appropriate dataset to run machine learning training jobs. The data will be stored in Amazon S3. The data engine...
Data IngestionData TransformationETLAWS Glue - Question #221Machine Learning Implementation and Operations
A company will use Amazon SageMaker to train and host a machine learning model for a marketing campaign. The data must be encrypted at rest. Most of the data is sensitive customer...
AWS KMSData Encryption at RestSageMaker SecurityOperational Overhead - Question #222Data Engineering
A data scientist is working on a model to predict a company's required inventory stock levels. All historical data is stored in .csv files in the company's data lake on Amazon S3....
Serverless SQLData LakeAWS GlueAmazon Athena - Question #223Machine Learning Implementation and Operations
A geospatial analysis company processes thousands of new satellite images each day to produce vessel detection data for commercial shipping. The company stores the training data in...
SageMaker TrainingData Input ModesCost OptimizationStorage Management - Question #224Data Engineering
A company is using Amazon SageMaker to build a machine learning (ML) model to predict customer churn based on customer call transcripts. Audio files from customer calls are located...
Data TransferEdge ComputingGPU ComputeHybrid Cloud - Question #225Data Engineering
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 runni...
Data IngestionStreaming DataKinesisData Transformation - Question #226Machine Learning Implementation and Operations
A company wants to predict the classification of documents that are created from an application. New documents are saved to an Amazon S3 bucket every 3 seconds. The company has dev...
SageMaker EndpointsReal-time InferenceMulti-Model DeploymentOperational Overhead - Question #227Modeling
A manufacturing company needs to identify returned smartphones that have been damaged by moisture. The company has an automated process that produces 2,000 diagnostic values for ea...
Model OptimizationDimensionality ReductionClassification AlgorithmsFeature Engineering - Question #228ML Implementation and Operations
A company is building a machine learning (ML) model to classify images of plants. An ML specialist has trained the model using the Amazon SageMaker built-in Image Classification al...
SageMaker EndpointsInference PerformanceElastic InferenceCloudWatch Metrics - Question #229Modeling
An automotive company is using computer vision in its autonomous cars. The company has trained its models successfully by using transfer learning from a convolutional neural networ...
SageMaker DebuggerModel Training OptimizationInference Latency ReductionDeep Learning Diagnostics - Question #230ML Implementation and Operations
A company's machine learning (ML) specialist is designing a scalable data storage solution for Amazon SageMaker. The company has an existing TensorFlow-based model that uses a trai...
SageMaker Script ModeData IngestionTFRecordAmazon S3 - Question #231Machine Learning Implementation and Operations
An ecommerce company wants to train a large image classification model with 10,000 classes. The company runs multiple model training iterations and needs to minimize operational ov...
SageMaker Managed Spot TrainingML Training CheckpointingCost OptimizationOperational Overhead Reduction - Question #232Machine Learning Implementation and Operations
A retail company uses a machine learning (ML) model for daily sales forecasting. The model has provided inaccurate results for the past 3 weeks. At the end of each day, an AWS Glue...
Model MonitoringData DriftAmazon SageMaker Model MonitorMLOps - Question #233Machine Learning Implementation and Operations
A machine learning (ML) specialist has prepared and used a custom container image with Amazon SageMaker to train an image classification model. The ML specialist is performing hype...
SageMaker ExperimentsHyperparameter Optimization (HPO)Model comparisonSageMaker Studio - Question #234Data Engineering
A company wants to deliver digital car management services to its customers. The company plans to analyze data to predict the likelihood of users changing cars. The company has 10...
Redshift Data ExportSageMaker Data PreparationAWS Secrets ManagerCost Optimization - Question #235Modeling
A company is building an application that can predict spam email messages based on email text. The company can generate a few thousand human-labeled datasets that contain a list of...
Transfer LearningBERTFine-tuningText Classification - Question #236ML Implementation and Operations
A company is using a legacy telephony platform and has several years remaining on its contract. The company wants to move to AWS and wants to implement the following machine learni...
Contact Lens for Amazon ConnectCall Center AnalyticsSentiment AnalysisNatural Language Processing - Question #237Modeling
A finance company needs to forecast the price of a commodity. The company has compiled a dataset of historical daily prices. A data scientist must train various forecasting models...
Dataset SplittingTime SeriesModel ValidationForecasting - Question #238ML Implementation and Operations
A retail company wants to build a recommendation system for the company's website. The system needs to provide recommendations for existing users and needs to base those recommenda...
Recommendation SystemsAmazon PersonalizeManaged ServicesUser Personalization - Question #239Machine Learning Implementation and Operations
A bank wants to use a machine learning (ML) model to predict if users will default on credit card payments. The training data consists of 30,000 labeled records and is evenly balan...
Hyperparameter TuningAmazon SageMakerModel OptimizationMLOps - Question #240Data Engineering
A data scientist has 20 TB of data in CSV format in an Amazon S3 bucket. The data scientist needs to convert the data to Apache Parquet format. How can the data scientist convert t...
AWS GlueData TransformationParquetETL - Question #241Data Engineering
A company is building a pipeline that periodically retrains its machine learning (ML) models by using new streaming data from devices. The company's data engineering team wants to...
Streaming DataKinesisLambdaData Transformation - Question #242Data Engineering
A retail company is ingesting purchasing records from its network of 20,000 stores to Amazon S3 by using Amazon Kinesis Data Firehose. The company uses a small, server-based applic...
Data TransformationKinesis Data FirehoseAWS LambdaServerless Architecture - Question #243ML Implementation and Operations
A sports broadcasting company is planning to introduce subtitles in multiple languages for a live broadcast. The commentary is in English. The company needs the transcriptions to a...
Speech-to-TextMachine TranslationCustomizationReal-time Processing - Question #244Modeling
A data scientist at a retail company is forecasting sales for a product over the next 3 months. After preliminary analysis, the data scientist identifies that sales are seasonal an...
ForecastingAmazon ForecastDeepAR+Time Series Analysis - Question #245Modeling
A company is building a predictive maintenance model for its warehouse equipment. The model must predict the probability of failure of all machines in the warehouse. The company ha...
Imbalanced DataOversamplingSMOTEData Preprocessing - Question #246Modeling
A company stores its documents in Amazon S3 with no predefined product categories. A data scientist needs to build a machine learning model to categorize the documents for all the...
Unsupervised LearningTopic ModelingAmazon SageMaker NTMOperational Efficiency - Question #247Machine Learning Implementation and Operations
A sports analytics company is providing services at a marathon. Each runner in the marathon will have their race ID printed as text on the front of their shirt. The company needs t...
Amazon RekognitionText DetectionManaged ServicesOperational Overhead - Question #248Machine Learning Implementation and Operations
A manufacturing company wants to monitor its devices for anomalous behavior. A data scientist has trained an Amazon SageMaker scikit-learn model that classifies a device as normal...
SageMaker InferenceBatch ProcessingCost OptimizationSageMaker Batch Transform - Question #249Modeling
A company wants to segment a large group of customers into subgroups based on shared characteristics. The company's data scientist is planning to use the Amazon SageMaker built-in...
k-means clusteringElbow MethodHyperparameter tuningUnsupervised learning - Question #250ML Implementation and Operations
A data scientist at a financial services company used Amazon SageMaker to train and deploy a model that predicts loan defaults. The model analyzes new loan applications and predict...
MLOpsModel DriftSageMaker PipelinesSageMaker Model Monitor