MLS-C01

A Machine Learning Specialist is assigned a TensorFlow project using Amazon SageMaker for training, and needs to continue working for an extended period with no Wi-Fi access.Which approach should the Specialist use to continue working?Read More →

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 algorithm by training an XGBoost algorithm.The ML specialist must find values for the eta, alpha, min_child_weight, and max_depth hyperparameters that will generate the most accurate model.Which approach will meet these requirements with the LEAST operational overhead?Read More →

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 feature of the dataset.The ML developer will use the importance scores to feature engineer the dataset.Which solution will meet this requirement with the LEAST development effort?Read More →

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 Studio domain.The company wants to build a central proxy application that data scientists and engineers can log in to by using their corporate credentials.The proxy application will authenticate users by using the company’s existing Identity provider (IdP).The application will then route users to the appropriate SageMaker Studio domain.The company plans to maintain a table in Amazon DynamoDB that contains SageMaker domains for each department.How should the company meet these requirements?Read More →

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 algorithm to train a model to detect scratches and dents in images of cars.After the model was trained, the ML specialist noticed that the model performed better on the training dataset than on the testing dataset.Which approach should the ML specialist use to improve the performance of the model on the testing data?Read More →

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 students.The data scientist wants to use the data to build student profiles.The university will use the profiles to direct resources to recruit students who are likely to enroll in the university.Which combination of steps should the data scientist take to predict whether a particular student applicant is likely to enroll in the university? (Choose two.)Read More →

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 machine learning (ML) solution to automate signature detection for each contract.The ML solution must also provide a confidence score for each contract page.Which Amazon Textract API action can the law firm use to generate a confidence score for each page of each contract?Read More →

A machine learning (ML) engineer has created a feature repository in Amazon SageMaker Feature Store for the company.The company has AWS accounts for development, integration, and production.The company hosts a feature store in the development account.The company uses Amazon S3 buckets to store feature values offline.The company wants to share features and to allow the integration account and the production account to reuse the features that are in the feature repository.Which combination of steps will meet these requirements? (Choose two.)Read More →

A Machine Learning Specialist is working with a large cybersecurity company that manages security events in real time for companies around the world.The cybersecurity company wants to design a solution that will allow it to use machine learning to score malicious events as anomalies on the data as it is being ingested.The company also wants be able to save the results in its data lake for later processing and analysis.What is the MOST efficient way to accomplish these tasks?Read More →

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 and that holidays affect sales.The data scientist also determines that sales of the product are correlated with sales of other products in the same category.The data scientist needs to train a sales forecasting model that incorporates this information.Which solution will meet this requirement with the LEAST development effort?Read More →