MLS-C01 Exam Questions
388 real MLS-C01 exam questions with expert-verified answers and explanations. Page 3 of 8.
- Question #101Modeling
A manufacturer of car engines collects data from cars as they are being driven. The data collected includes timestamp, engine temperature, rotations per minute (RPM), and other sen...
Supervised LearningPredictive ModelingData LabelingML Problem Formulation - Question #102Exploratory Data Analysis
A company wants to predict the sale prices of houses based on available historical sales data. The target variable in the company's dataset is the sale price. The features include...
Feature SelectionCorrelation AnalysisData PreprocessingModel Complexity - Question #103Modeling
A company wants to classify user behavior as either fraudulent or normal. Based on internal research, a machine learning specialist will build a binary classifier based on two feat...
Model SelectionDecision TreesSupport Vector MachinesClassification Algorithms - Question #104Modeling
A health care company is planning to use neural networks to classify their X-ray images into normal and abnormal classes. The labeled data is divided into a training set of 1,000 i...
OverfittingRegularization TechniquesNeural Network ArchitectureModel Evaluation - Question #105Modeling
This graph shows the training and validation loss against the epochs for a neural network. The network being trained is as follows: Two dense layers, one output neuron 100 neurons...
Early StoppingOverfittingNeural NetworksModel Optimization - Question #106Modeling
A Machine Learning Specialist is attempting to build a linear regression model. Given the displayed residual plot only, what is the MOST likely problem with the model?
Linear RegressionResidual AnalysisModel DiagnosticsHeteroscedasticity - Question #107Machine Learning Implementation and Operations
A large company has developed a BI application that generates reports and dashboards using data collected from various operational metrics. The company wants to provide executives...
Conversational AINatural Language ProcessingSpeech RecognitionText-to-Speech - Question #108Modeling
A machine learning specialist works for a fruit processing company and needs to build a system that categorizes apples into three types. The specialist has collected a dataset that...
UnderfittingBias ReductionModel ImprovementDataset Size - Question #109Modeling
A company uses camera images of the tops of items displayed on store shelves to determine which items were removed and which ones still remain. After several hours of data labeling...
Data AugmentationImage ClassificationModel TrainingComputer Vision - Question #110Modeling
A Data Scientist is developing a binary classifier to predict whether a patient has a particular disease on a series of test results. The Data Scientist has data on 400 patients ra...
Cross-validationImbalanced dataModel evaluationStratified sampling - Question #111Machine Learning Implementation and Operations
A technology startup is using complex deep neural networks and GPU compute to recommend the company's products to its existing customers based upon each customer's habits and inter...
AWS Deep Learning ContainersML Workflow AutomationCost OptimizationGPU-accelerated workloads - Question #112Modeling
A Machine Learning Specialist prepared the following graph displaying the results of k-means for k = [1..10]: Considering the graph, what is a reasonable selection for the optimal...
k-means clusteringElbow methodHyperparameter tuningUnsupervised learning - Question #113Machine Learning Implementation and Operations
A media company with a very large archive of unlabeled images, text, audio, and video footage wishes to index its assets to allow rapid identification of relevant content by the Re...
AWS AI ServicesContent IndexingComputer VisionNatural Language Processing - Question #114Data Engineering
A Machine Learning Specialist is working for an online retailer that wants to run analytics on every customer visit, processed through a machine learning pipeline. The data needs t...
Kinesis Data StreamsShardingData IngestionThroughput calculation - Question #115Modeling
A Machine Learning Specialist is deciding between building a naive Bayesian model or a full Bayesian network for a classification problem. The Specialist computes the Pearson corre...
Bayesian NetworksNaive BayesFeature DependenceModel Selection - Question #116Modeling
A Data Scientist is building a linear regression model and will use resulting p-values to evaluate the statistical significance of each coefficient. Upon inspection of the dataset,...
Data TransformationLinear Regression AssumptionsFeature Engineering - Question #117Modeling
A Machine Learning Specialist is assigned to a Fraud Detection team and must tune an XGBoost model, which is working appropriately for test data. However, with unknown data, it is...
XGBoostOverfittingHyperparameter TuningRegularization - Question #118Machine Learning Implementation and Operations
A data scientist is developing a pipeline to ingest streaming web traffic data. The data scientist needs to implement a process to identify unusual web traffic patterns as part of...
Streaming Anomaly DetectionReal-time Data ProcessingAmazon Kinesis Data AnalyticsAdaptive Machine Learning - Question #119Modeling
A Data Scientist received a set of insurance records, each consisting of a record ID, the final outcome among 200 categories, and the date of the final outcome. Some partial inform...
ForecastingTime SeriesCount PredictionMachine Learning Models - Question #120Machine Learning Implementation and Operations
A company that promotes healthy sleep patterns by providing cloud-connected devices currently hosts a sleep tracking application on AWS. The application collects device usage infor...
Amazon SageMakerModel DeploymentMLOpsA/B Testing - Question #121Data Engineering
An agricultural company is interested in using machine learning to detect specific types of weeds in a 100-acre grassland field. Currently, the company uses tractor-mounted cameras...
RecordIOImage Data PreparationAmazon S3Deep Learning - Question #122ML Implementation and Operations
A manufacturer is operating a large number of factories with a complex supply chain relationship where unexpected downtime of a machine can cause production to stop at several fact...
Edge MLAWS IoT GreengrassReal-time InferenceDisconnected Operations - Question #123Machine Learning Implementation and Operations
A Machine Learning Specialist is designing a scalable data storage solution for Amazon SageMaker. There is an existing TensorFlow-based model implemented as a train.py script that...
SageMaker Script ModeTensorFlowTFRecordsTraining Data Provisioning - Question #124Modeling
The chief editor for a product catalog wants the research and development team to build a machine learning system that can be used to detect whether or not individuals in a collect...
Image ClassificationConvolutional Neural NetworksAlgorithm SelectionComputer Vision - Question #125Machine Learning Implementation and Operations
A retail company is using Amazon Personalize to provide personalized product recommendations for its customers during a marketing campaign. The company sees a significant increase...
Amazon PersonalizeReal-time data ingestionRecommendation systemsModel adaptation - Question #126ML Implementation and Operations
A machine learning (ML) specialist wants to secure calls to the Amazon SageMaker Service API. The specialist has configured Amazon VPC with a VPC interface endpoint for the Amazon...
VPC EndpointsEndpoint PoliciesSecurity GroupsSageMaker Security - Question #127Data Engineering
An e commerce company wants to launch a new cloud-based product recommendation feature for its web application. Due to data localization regulations, any sensitive data must not le...
AWS GlueData IngestionHybrid CloudData Security - Question #128Modeling
A logistics company needs a forecast model to predict next month's inventory requirements for a single item in 10 warehouses. A machine learning specialist uses Amazon Forecast to...
Amazon ForecastHyperparameter TuningAutoMLModel Optimization - Question #129Data Engineering
A data scientist wants to use Amazon Forecast to build a forecasting model for inventory demand for a retail company. The company has provided a dataset of historic inventory deman...
Amazon ForecastData TransformationETLAWS Glue - Question #130Machine Learning Implementation and Operations
A machine learning specialist is running an Amazon SageMaker endpoint using the built-in object detection algorithm on a P3 instance for real-time predictions in a company's produc...
SageMaker EndpointsResource OptimizationInstance TypesReal-time Inference - Question #131ML Implementation and Operations
A data scientist uses an Amazon SageMaker notebook instance to conduct data exploration and analysis. This requires certain Python packages that are not natively available on Amazo...
SageMaker NotebooksLifecycle ConfigurationPackage ManagementEnvironment Setup - Question #132Machine Learning Implementation and Operations
A data scientist needs to identify fraudulent user accounts for a company's ecommerce platform. The company wants the ability to determine if a newly created account is associated...
AWS GlueMachine Learning TransformsRecord LinkageFraud Detection - Question #133Modeling
A Data Scientist is developing a machine learning model to classify whether a financial transaction is fraudulent. The labeled data available for training consists of 100,000 non-...
XGBoostImbalanced learningFalse negativesHyperparameter tuning - Question #134Modeling
A data scientist has developed a machine learning translation model for English to Japanese by using Amazon SageMaker's built-in seq2seq algorithm with 500,000 aligned sentence pai...
Sequence-to-sequence (seq2seq)Attention mechanismNeural Machine TranslationHyperparameter tuning - Question #135Modeling
A financial company is trying to detect credit card fraud. The company observed that, on average, 2% of credit card transactions were fraudulent. A data scientist trained a classif...
Classification metricsImbalanced dataPrecision-RecallFraud detection - Question #136Machine Learning Implementation and Operations
A machine learning specialist is developing a proof of concept for government users whose primary concern is security. The specialist is using Amazon SageMaker to train a convoluti...
SageMaker SecurityNetwork IsolationData ExfiltrationTraining Jobs - Question #137Machine Learning Implementation and Operations
A medical imaging company wants to train a computer vision model to detect areas of concern on patients' CT scans. The company has a large collection of unlabeled CT scans that are...
SageMaker Ground TruthData LabelingPrivate WorkforceData Security - Question #138ML Implementation and Operations
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 applicatio...
Amazon TextractAmazon Augmented AI (A2I)Human-in-the-loopDocument Processing - Question #139Data Engineering
A company ingests machine learning (ML) data from web advertising clicks into an Amazon S3 data lake. Click data is added to an Amazon Kinesis data stream by using the Kinesis Prod...
Kinesis Data FirehoseAmazon S3Data IngestionPerformance Tuning - Question #140Modeling
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 prod...
Data SplittingRecommendation SystemsTraining and TestingDataset Preparation - Question #141ML Implementation and Operations
A financial services company wants to adopt Amazon SageMaker as its default data science environment. The company's data scientists run machine learning (ML) models on confidential...
SageMaker SecurityData Egress ControlNetwork IsolationAWS PrivateLink - Question #142Modeling
A Machine Learning Specialist is developing a regression model to predict rental rates from rental listings. A variable named Wall_Color represents the most prominent exterior wall...
Feature EngineeringCategorical Data EncodingRegression ModelsData Preprocessing - Question #143Data Engineering
A network security vendor needs to ingest telemetry data from millions of endpoints running all over the world. This data is transmitted every 30 seconds in the form of records con...
Data IngestionStream ProcessingData LakesAnalytics - Question #144Modeling
A newspaper publisher has a table of customer data that consists of several numerical and categorical features, such as age and education history, as well as subscription status. T...
Binary ClassificationXGBoostSageMaker Built-in AlgorithmsTabular Data - Question #145Modeling
A Machine Learning Specialist is working on a linear regression model and notices the model is overfitting. The specialist applies an L1 regularization parameter and runs the model...
RegularizationL1 RegularizationHyperparameter TuningOverfitting - Question #146Modeling
A Data Scientist has explored and sanitized a dataset in preparation for the modeling phase of a supervised learning task. The statistical dispersion can vary widely between featur...
Data SplittingFeature ScalingData PreprocessingModel Evaluation - Question #147Data Engineering
A Machine Learning Specialist stores IoT soil sensor data in an Amazon DynamoDB table and stores weather event data as JSON files in Amazon S3. The dataset in DynamoDB is 10 GB in...
AWS GlueData CatalogData TransformationServerless ETL - Question #148ML Implementation and Operations
You are tasked with moving a legacy application from a virtual machine running inside your datacenter to an Amazon VPC. Unfortunately, this app requires access to a number of onpre...
Hybrid CloudAWS NetworkingApplication MigrationVPC Connectivity - Question #149ML Implementation and Operations
A manufacturer has deployed an array of 50000 sensors throughout its plant to predict failures in components. Data Scientists have built a long short-term memory (LSTM) model in Gl...
Distributed TrainingHyperparameter OptimizationModel Training PerformanceBatch Size Scaling - Question #150Modeling
A Data Scientist needs to create a model for fraud detection The dataset is composed of 2 years' worth of logged transactions, each with a small set of features All of the transact...
Imbalanced DataFraud DetectionF1 ScoreResampling Techniques