MLS-C01 (Page 20)

A machine learning (ML) specialist is using the Amazon SageMaker DeepAR forecasting algorithm to train a model on CPU-based Amazon EC2 On-Demand instances.The model currently takes multiple hours to train.The ML specialist wants to decrease the training time of the model.Which approaches will meet this requirement? (Choose two.)Read More →

An online delivery company wants to choose the fastest courier for each delivery at the moment an order is placed.The company wants to implement this feature for existing users and new users of its application.Data scientists have trained separate models with XGBoost for this purpose, and the models are stored in Amazon S3.There is one model for each city where the company operates.Operation engineers are hosting these models in Amazon EC2 for responding to the web client requests, with one instance for each model, but the instances have only a 5% utilization in CPU and memory.The operation engineers want to avoid managing unnecessary resources.Which solution will enable the company to achieve its goal with the LEAST operational overhead?Read More →

A machine learning engineer is building a bird classification model.The engineer randomly separates a dataset into a training dataset and a validation dataset.During the training phase, the model achieves very high accuracy.However, the model did not generalize well during validation of the validation dataset.The engineer realizes that the original dataset was imbalanced.What should the engineer do to improve the validation accuracy of the model?Read More →

During mini-batch training of a neural network for a classification problem, a Data Scientist notices that training accuracy oscillates.What is the MOST likely cause of this issue?Read More →

A Machine Learning Specialist at a company sensitive to security is preparing a dataset for model training.The dataset is stored in Amazon S3 and containsPersonally Identifiable Information (PII).The dataset:✑ Must be accessible from a VPC only.✑ Must not traverse the public internet.How can these requirements be satisfied?Read More →

A Machine Learning Specialist is working with a large company to leverage machine learning within its products.The company wants to group its customers into categories based on which customers will and will not churn within the next 6 months.The company has labeled the data available to the Specialist.Which machine learning model type should the Specialist use to accomplish this task?Read More →

A Machine Learning Specialist receives customer data for an online shopping website.The data includes demographics, past visits, and locality information.TheSpecialist must develop a machine learning approach to identify the customer shopping patterns, preferences, and trends to enhance the website for better service and smart recommendations.Which solution should the Specialist recommend?Read More →

A Machine Learning Specialist is developing a custom video recommendation model for an application.The dataset used to train this model is very large with millions of data points and is hosted in an Amazon S3 bucket.The Specialist wants to avoid loading all of this data onto an Amazon SageMaker notebook instance because it would take hours to move and will exceed the attached 5 GB Amazon EBS volume on the notebook instance.Which approach allows the Specialist to use all the data to train the model?Read More →

A manufacturing company has structured and unstructured data stored in an Amazon S3 bucket.A Machine Learning Specialist wants to use SQL to run queries on this data.Which solution requires the LEAST effort to be able to query this data?Read More →

A Machine Learning Specialist is building a model that will perform time series forecasting using Amazon SageMaker.The Specialist has finished training the model and is now planning to perform load testing on the endpoint so they can configure Auto Scaling for the model variant.Which approach will allow the Specialist to review the latency, memory utilization, and CPU utilization during the load test?Read More →