MLS-C01 (Page 14)

A company wants to use automatic speech recognition (ASR) to transcribe messages that are less than 60 seconds long from a voicemail-style application.The company requires the correct identification of 200 unique product names, some of which have unique spellings or pronunciations.The company has 4,000 words of Amazon SageMaker Ground Truth voicemail transcripts it can use to customize the chosen ASR model.The company needs to ensure that everyone can update their customizations multiple times each hour.Which approach will maximize transcription accuracy during the development phase?Read More →

A machine learning (ML) specialist is administering a production Amazon SageMaker endpoint with model monitoring configured.Amazon SageMaker ModelMonitor detects violations on the SageMaker endpoint, so the ML specialist retrains the model with the latest dataset.This dataset is statistically representative of the current production traffic.The ML specialist notices that even after deploying the new SageMaker model and running the first monitoring job, the SageMaker endpoint still has violations.What should the ML specialist do to resolve the violations?Read More →

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 information from device users.The company’s Data Science team is building a machine learning model to predict if and when a user will stop utilizing the company’s devices.Predictions from this model are used by a downstream application that determines the best approach for contacting users.The Data Science team is building multiple versions of the machine learning model to evaluate each version against the company’s business goals.To measure long-term effectiveness, the team wants to run multiple versions of the model in parallel for long periods of time, with the ability to control the portion of inferences served by the models.Which solution satisfies these requirements with MINIMAL effort?Read More →

A Machine Learning Specialist built an image classification deep learning model.However, the Specialist ran into an overfitting problem in which the training and testing accuracies were 99% and 75%, respectively.How should the Specialist address this issue and what is the reason behind it?Read More →

A company is using Amazon Polly to translate plaintext documents to speech for automated company announcements.However, company acronyms are being mispronounced in the current documents.How should a Machine Learning Specialist address this issue for future documents?Read More →

A company is training machine learning (ML) models on Amazon SageMaker by using 200 TB of data that is stored in Amazon S3 buckets.The training data consists of individual files that are each larger than 200 MB in size.The company needs a data access solution that offers the shortest processing time and the least amount of setup.Which solution will meet these requirements?Read More →

A media company wants to create a solution that identifies celebrities in pictures that users upload.The company also wants to identify the IP address and the timestamp details from the users so the company can prevent users from uploading pictures from unauthorized locations.Which solution will meet these requirements with LEAST development effort?Read More →

A company is converting a large number of unstructured paper receipts into images.The company wants to create a model based on natural language processing(NLP) to find relevant entities such as date, location, and notes, as well as some custom entities such as receipt numbers.The company is using optical character recognition (OCR) to extract text for data labeling.However, documents are in different structures and formats, and the company is facing challenges with setting up the manual workflows for each document type.Additionally, the company trained a named entity recognition (NER) model for custom entity detection using a small sample size.This model has a very low confidence score and will require retraining with a large dataset.Which solution for text extraction and entity detection will require the LEAST amount of effort?Read More →

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 developed three versions of a machine learning (ML) model within Amazon SageMaker to classify document text.The company wants to deploy these three versions to predict the classification of each document.Which approach will meet these requirements with the LEAST operational overhead?Read More →

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 an Amazon S3 bucket.Company security policy states that SageMaker notebook instances must not have internet connectivity.Which solution will meet the company’s security requirements?Read More →