Machine Learning Specialty (Page 17)

A data scientist is working on a forecast problem by using a dataset that consists of .csv files that are stored in Amazon S3.The files contain a timestamp variable in the following format:March 1st, 2020, 08:14pm -There is a hypothesis about seasonal differences in the dependent variable.This number could be higher or lower for weekdays because some days and hours present varying values, so the day of the week, month, or hour could be an important factor.As a result, the data scientist needs to transform the timestamp into weekdays, month, and day as three separate variables to conduct an analysis.Which solution requires the LEAST operational overhead to create a new dataset with the added features?Read More →

A manufacturing company asks its machine learning specialist to develop a model that classifies defective parts into one of eight defect types.The company has provided roughly 100,000 images per defect type for training.During the initial training of the image classification model, the specialist notices that the validation accuracy is 80%, while the training accuracy is 90%.It is known that human-level performance for this type of image classification is around 90%.What should the specialist consider to fix this issue?Read More →

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 engineer wants to use recall as the objective metric.The ML engineer also wants to expand the hyperparameter range for a new hyperparameter tuning job.The new hyperparameter range will include the range of the previously performed tuning job.Which approach will run the new hyperparameter tuning job in the LEAST amount of time?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 →

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 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 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 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 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 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 →