MLS-C01 Exam Questions
388 real MLS-C01 exam questions with expert-verified answers and explanations. Page 7 of 8.
- Question #309Data Engineering
A machine learning (ML) specialist at a retail company must build a system to forecast the daily sales for one of the company's stores. The company provided the ML specialist with...
Missing Data ImputationData PreprocessingTime Series ForecastingModel Performance - Question #310Machine Learning Implementation and Operations
A mining company wants to use machine learning (ML) models to identify mineral images in real time. A data science team built an image recognition model that is based on convolutio...
SageMaker Inference RecommenderModel DeploymentMLOpsResource Optimization - Question #311Machine Learning Implementation and Operations
A company is building custom deep learning models in Amazon SageMaker by using training and inference containers that run on Amazon EC2 instances. The company wants to reduce train...
Cost OptimizationSageMaker TrainingSpot InstancesCheckpoints - Question #312Modeling
A company hosts a public web application on AWS. The application provides a user feedback feature that consists of free-text fields where users can submit text to provide feedback....
SageMaker AlgorithmsText ClassificationMulti-class ClassificationSupervised Learning - Question #313ML Implementation and Operations
A digital media company wants to build a customer churn prediction model by using tabular data. The model should clearly indicate whether a customer will stop using the company's s...
Data PreparationClassificationSageMaker Data WranglerSageMaker Built-in Algorithms - Question #314Modeling
A data engineer is evaluating customer data in Amazon SageMaker Data Wrangler. The data engineer will use the customer data to create a new model to predict customer behavior. The...
MulticollinearitySageMaker Data WranglerDimensionality ReductionRegularization - Question #315Data Engineering
A company processes millions of orders every day. The company uses Amazon DynamoDB tables to store order information. When customers submit new orders, the new orders are immediate...
Data StreamingNear Real-time AnalyticsDynamoDBKinesis Data Firehose - Question #316Data Engineering
A data engineer is preparing a dataset that a retail company will use to predict the number of visitors to stores. The data engineer created an Amazon S3 bucket. The engineer subsc...
AWS Data ExchangeS3 Event NotificationsServerless Data ProcessingCost Optimization - Question #317Machine Learning Implementation and Operations
A company operates large cranes at a busy port The company plans to use machine learning (ML) for predictive maintenance of the cranes to avoid unexpected breakdowns and to improve...
ML Project SuitabilityData RequirementsPredictive MaintenanceSupervised Learning Prerequisites - Question #318Modeling
A company wants to create an artificial intelligence (A? yoga instructor that can lead large classes of students. The company needs to create a feature that can accurately count th...
Computer VisionObject DetectionPose EstimationModel Selection - Question #319ML Implementation and Operations
An ecommerce company has used Amazon SageMaker to deploy a factorization machines (FM) model to suggest products for customers. The company's data science team has developed two ne...
SageMaker EndpointsA/B TestingModel DeploymentTraffic Routing - Question #320Machine Learning Implementation and Operations
A data scientist stores financial datasets in Amazon S3. The data scientist uses Amazon Athena to query the datasets by using SQL. The data scientist uses Amazon SageMaker to deplo...
IAM PermissionsSageMaker EndpointAmazon AthenaService Integration - Question #321Modeling
A data scientist is building a linear regression model. The scientist inspects the dataset and notices that the mode of the distribution is lower than the median, and the median is...
Data TransformationSkewnessLinear Regression PreprocessingStatistical Distributions - Question #322Modeling
A data scientist receives a collection of insurance claim records. Each record includes a claim ID. the final outcome of the insurance claim, and the date of the final outcome. The...
ForecastingTime SeriesPredictive ModelingProblem Framing - Question #323Machine Learning Implementation and Operations
A retail company stores 100 GB of daily transactional data in Amazon S3 at periodic intervals. The company wants to identify the schema of the transactional data. The company also...
Data CatalogingETL and Data TransformationFraud Detection MLServerless Data Processing - Question #324Machine Learning Implementation and Operations
A data scientist uses Amazon SageMaker Data Wrangler to define and perform transformations and feature engineering on historical data. The data scientist saves the transformations...
SageMaker PipelinesAmazon EventBridgeSageMaker Feature StoreMLOps - Question #325ML Implementation and Operations
An insurance company developed a new experimental machine learning (ML) model to replace an existing model that is in production. The company must validate the quality of predictio...
MLOpsModel deploymentModel validationShadow deployment - Question #326ML Implementation and Operations
A company deployed a machine learning (ML) model on the company website to predict real estate prices. Several months after deployment, an ML engineer notices that the accuracy of...
Model DriftModel MonitoringSageMaker Model MonitorIncremental Training - Question #327Modeling
A university wants to develop a targeted recruitment strategy to increase new student enrollment. A data scientist gathers information about the academic performance history of stu...
Data LabelingClustering AlgorithmsStudent Enrollment PredictionAmazon SageMaker - Question #328Machine Learning Implementation and Operations
A machine learning (ML) specialist is using the Amazon SageMaker DeepAR forecasting algorithm to train a model on CPU-based Amazon EC2 On-Demand instances. The model currently take...
SageMaker TrainingPerformance OptimizationDistributed TrainingGPU Acceleration - Question #329Modeling
A chemical company has developed several machine learning (ML) solutions to identify chemical process abnormalities. The time series values of independent variables and the labels...
Classification MetricsPrecision-Recall Trade-offAnomaly DetectionBusiness Impact of ML - Question #330Machine Learning Implementation and Operations
An online delivery company wants to choose the fastest courier for each delivery at the moment an order is placed. The company wants to implement this feature for existing users an...
Model DeploymentMLOpsSageMakerMulti-Model Serving - Question #331ML Implementation and Operations
A company builds computer-vision models that use deep learning for the autonomous vehicle industry. A machine learning (ML) specialist uses an Amazon EC2 instance that has a CPU:GP...
EC2 Spot InstancesCost OptimizationDeep Learning TrainingResource Utilization - Question #332Exploratory Data Analysis
A company wants to forecast the daily price of newly launched products based on 3 years of data for older product prices, sales, and rebates. The time-series data has irregular tim...
Data PreparationTime Series DataMissing Value ImputationSageMaker Data Wrangler - Question #333Exploratory Data Analysis
A data scientist is building a forecasting model for a retail company by using the most recent 5 years of sales records that are stored in a data warehouse. The dataset contains sa...
Data VisualizationData AggregationTrend AnalysisComparative Analysis - Question #334Exploratory Data Analysis
A company uses sensors on devices such as motor engines and factory machines to measure parameters, temperature and pressure. The company wants to use the sensor data to predict eq...
Data PreprocessingOutlier DetectionSageMaker Data WranglerOperational Overhead - Question #335Data Engineering
A data scientist obtains a tabular dataset that contains 150 correlated features with different ranges to build a regression model. The data scientist needs to achieve more efficie...
Data PreprocessingFeature ScalingPrincipal Component Analysis (PCA)Amazon SageMaker Data Wrangler - Question #336Modeling
An online retailer collects the following data on customer orders: demographics, behaviors, location, shipment progress, and delivery time. A data scientist joins all the collected...
Dimensionality ReductionClusteringUnsupervised LearningCustomer Segmentation - Question #337Modeling
A machine learning engineer is building a bird classification model. The engineer randomly separates a dataset into a training dataset and a validation dataset. During the training...
Dataset ImbalanceStratified SamplingModel GeneralizationData Splitting - Question #338Exploratory Data Analysis
A data engineer wants to perform exploratory data analysis (EDA) on a petabyte of data. The data engineer does not want to manage compute resources and wants to pay only for querie...
Exploratory Data AnalysisAmazon SageMakerApache SparkServerless Computing - Question #339Exploratory Data Analysis
A data scientist receives a new dataset in .csv format and stores the dataset in Amazon S3. The data scientist will use the dataset to train a machine learning (ML) model. The data...
SageMaker Data WranglerData QualityExploratory Data AnalysisMissing Data & Outliers - Question #340Modeling
An ecommerce company has developed a XGBoost model in Amazon SageMaker to predict whether a customer will return a purchased item. The dataset is imbalanced. Only 5% of customers r...
XGBoost Hyperparameter TuningImbalanced Data HandlingAutomatic Model Tuning (AMT)Recall Optimization - Question #341ML Implementation and Operations
A data scientist is trying to improve the accuracy of a neural network classification model. The data scientist wants to run a large hyperparameter tuning job in Amazon SageMaker....
Hyperparameter TuningSageMaker Hyperparameter TuningHyperbandResource Optimization - Question #342ML Implementation and Operations
A machine learning (ML) specialist needs to solve a binary classification problem for a marketing dataset. The ML specialist must maximize the Area Under the ROC Curve (AUC) of the...
Hyperparameter TuningAmazon SageMakerXGBoostOperational Efficiency - Question #343Exploratory Data Analysis
A machine learning (ML) developer for an online retailer recently uploaded a sales dataset into Amazon SageMaker Studio. The ML developer wants to obtain importance scores for each...
SageMaker Data WranglerFeature EngineeringFeature ImportanceLow-code/No-code ML - Question #344Machine Learning Implementation and Operations
A company is setting up a mechanism for data scientists and engineers from different departments to access an Amazon SageMaker Studio domain. Each department has a unique SageMaker...
SageMaker StudioAPI IntegrationPresigned URLsAccess Control - Question #345Modeling
An insurance company is creating an application to automate car insurance claims. A machine learning (ML) specialist used an Amazon SageMaker Object Detection - TensorFlow built-in...
OverfittingRegularizationHyperparameter Tuning - Question #346Modeling
A developer at a retail company is creating a daily demand forecasting model. The company stores the historical hourly demand data in an Amazon S3 bucket. However, the historical d...
Time Series PreprocessingSageMaker Data WranglerMissing Data HandlingARIMA Modeling - Question #347Machine Learning Implementation and Operations
A company decides to use Amazon SageMaker to develop machine learning (ML) models. The company will host SageMaker notebook instances in a VPC. The company stores training data in...
SageMaker NetworkingVPC EndpointsNetwork SecurityPrivate Connectivity - Question #348ML Implementation and Operations
A machine learning (ML) engineer uses Bayesian optimization for a hyperpara meter tuning job in Amazon SageMaker. The ML engineer uses precision as the objective metric. The ML eng...
Hyperparameter TuningAmazon SageMakerWarm StartBayesian Optimization - Question #349Modeling
A news company is developing an article search tool for its editors. The search tool should look for the articles that are most relevant and representative for particular words tha...
Natural Language ProcessingText Feature ExtractionTF-IDFInformation Retrieval - Question #350Machine Learning Implementation and Operations
A growing company has a business-critical key performance indicator (KPI) for the uptime of a machine learning (ML) recommendation system. The company is using Amazon SageMaker hos...
SageMaker EndpointsHigh AvailabilityMulti-AZ DeploymentRTO - Question #351ML Implementation and Operations
A global company receives and processes hundreds of documents daily. The documents are in printed .pdf format or .jpg format. A machine learning (ML) specialist wants to build an a...
Document ProcessingOCRNLPManaged Services - Question #352Modeling
A company wants to detect credit card fraud. The company has observed that an average of 2% of credit card transactions are fraudulent. A data scientist trains a classifier on a ye...
Machine Learning MetricsClassificationImbalanced DataFraud Detection - Question #353Data Engineering
A data scientist is designing a repository that will contain many images of vehicles. The repository must scale automatically in size to store new images every day. The repository...
AWS StorageAmazon S3Data ReplicationVersioning - Question #354Machine Learning Implementation and Operations
An ecommerce company wants to update a production real-time machine learning (ML) recommendation engine API that uses Amazon SageMaker. The company wants to release a new model but...
SageMaker EndpointsProduction VariantsA/B TestingMLOps - Question #355Data Engineering
A machine learning (ML) specialist at a manufacturing company uses Amazon SageMaker DeepAR to forecast input materials and energy requirements for the company. Most of the data in...
Data ImputationMissing ValuesSageMaker DeepARData Preprocessing - Question #356Machine Learning Implementation and Operations
A law firm handles thousands of contracts every day. Every contract must be signed. Currently, a lawyer manually checks all contracts for signatures. The law firm is developing a m...
Amazon TextractSignature DetectionAsynchronous APIDocument Analysis - Question #357Modeling
A company that operates oil platforms uses drones to photograph locations on oil platforms that are difficult for humans to access to search for corrosion. Experienced engineers re...
Object DetectionImage ClassificationSupervised LearningAWS Rekognition - Question #358Machine Learning Implementation and Operations
A company maintains a 2 TB dataset that contains information about customer behaviors. The company stores the dataset in Amazon S3. The company stores a trained model container in...
Batch InferenceCost OptimizationAWS BatchAmazon EC2 Spot Instances