Machine Learning Specialty (Page 9)

A web-based company wants to improve its conversion rate on its landing page.Using a large historical dataset of customer visits, the company has repeatedly trained a multi-class deep learning network algorithm on Amazon SageMaker.However, there is an overfitting problem: training data shows 90% accuracy in predictions, while test data shows 70% accuracy only.The company needs to boost the generalization of its model before deploying it into production to maximize conversions of visits to purchases.Which action is recommended to provide the HIGHEST accuracy model for the company’s test and validation data?Read More →

A retail company intends to use machine learning to categorize new products.A labeled dataset of current products was provided to the Data Science team.The dataset includes 1,200 products.The labeled dataset has 15 features for each product such as title dimensions, weight, and price.Each product is labeled as belonging to one of six categories such as books, games, electronics, and movies.Which model should be used for categorizing new products using the provided dataset for training?Read More →

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?Read More →

A machine learning (ML) engineer is integrating a production model with a customer metadata repository for real-time inference.The repository is hosted in Amazon SageMaker Feature Store.The engineer wants to retrieve only the latest version of the customer metadata record for a single customer at a time.Which solution will meet these requirements?Read More →

A machine learning (ML) specialist is training a linear regression model.The specialist notices that the model is overfitting.The specialist applies an L1 regularization parameter and runs the model again.This change results in all features having zero weights.What should the ML specialist do to improve the model results?Read More →

A data scientist for a medical diagnostic testing company has developed a machine learning (ML) model to identify patients who have a specific disease.The dataset that the scientist used to train the model is imbalanced.The dataset contains a large number of healthy patients and only a small number of patients who have the disease.The model should consider that patients who are incorrectly identified as positive for the disease will increase costs for the company.Which metric will MOST accurately evaluate the performance of this model?Read More →

A wildlife research company has a set of images of lions and cheetahs.The company created a dataset of the images.The company labeled each image with a binary label that indicates whether an image contains a lion or cheetah.The company wants to train a model to identify whether new images contain a lion or cheetah.Which Amazon SageMaker algorithm will meet this requirement?Read More →

An engraving company wants to automate its quality control process for plaques.The company performs the process before mailing each customized plaque to a customer.The company has created an Amazon S3 bucket that contains images of defects that should cause a plaque to be rejected.Low-confidence predictions must be sent to an internal team of reviewers who are using Amazon Augmented AI (Amazon A2I).Which solution will meet these requirements?Read More →

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 to SageMaker Feature Store.The historical data is periodically uploaded to an Amazon S3 bucket.The data scientist needs to transform the new historic data and add it to the online feature store.The data scientist needs to prepare the new historic data for training and inference by using native integrations.Which solution will meet these requirements with the LEAST development effort?Read More →

A machine learning (ML) specialist uploads 5 TB of data to an Amazon SageMaker Studio environment.The ML specialist performs initial data cleansing.Before the ML specialist begins to train a model, the ML specialist needs to create and view an analysis report that details potential bias in the uploaded data.Which combination of actions will meet these requirements with the LEAST operational overhead? (Choose two.)Read More →