Machine Learning Specialty (Page 16)

An employee found a video clip with audio on a company’s social media feed.The language used in the video is Spanish.English is the employee’s first language, and they do not understand Spanish.The employee wants to do a sentiment analysis.What combination of services is the MOST efficient to accomplish the task?Read More →

A Machine Learning Specialist is packaging a custom ResNet model into a Docker container so the company can leverage Amazon SageMaker for training.TheSpecialist is using Amazon EC2 P3 instances to train the model and needs to properly configure the Docker container to leverage the NVIDIA GPUs.What does the Specialist need to do?Read More →

A Machine Learning Specialist is building a logistic regression model that will predict whether or not a person will order a pizza.The Specialist is trying to build the optimal model with an ideal classification threshold.What model evaluation technique should the Specialist use to understand how different classification thresholds will impact the model’s performance?Read More →

An interactive online dictionary wants to add a widget that displays words used in similar contexts.A Machine Learning Specialist is asked to provide word features for the downstream nearest neighbor model powering the widget.What should the Specialist do to meet these requirements?Read More →

A Machine Learning team runs its own training algorithm on Amazon SageMaker.The training algorithm requires external assets.The team needs to submit both its own algorithm code and algorithm-specific parameters to Amazon SageMaker.What combination of services should the team use to build a custom algorithm in Amazon SageMaker? (Choose two.)Read More →

A technology startup is using complex deep neural networks and GPU compute to recommend the company’s products to its existing customers based upon each customer’s habits and interactions.The solution currently pulls each dataset from an Amazon S3 bucket before loading the data into a TensorFlow model pulled from the company’s Git repository that runs locally.This job then runs for several hours while continually outputting its progress to the same S3 bucket.The job can be paused, restarted, and continued at any time in the event of a failure, and is run from a central queue.Senior managers are concerned about the complexity of the solution’s resource management and the costs involved in repeating the process regularly.They ask for the workload to be automated so it runs once a week, starting Monday and completing by the close of business Friday.Which architecture should be used to scale the solution at the lowest cost?Read More →

An agricultural company is interested in using machine learning to detect specific types of weeds in a 100-acre grassland field.Currently, the company uses tractor-mounted cameras to capture multiple images of the field as 10 ֳ— 10 grids.The company also has a large training dataset that consists of annotated images of popular weed classes like broadleaf and non-broadleaf docks.The company wants to build a weed detection model that will detect specific types of weeds and the location of each type within the field.Once the model is ready, it will be hosted on Amazon SageMaker endpoints.The model will perform real-time inferencing using the images captured by the cameras.Which approach should a Machine Learning Specialist take to obtain accurate predictions?Read More →

A Machine Learning Specialist is designing a scalable data storage solution for Amazon SageMaker.There is an existing TensorFlow-based model implemented as a train.py script that relies on static training data that is currently stored as TFRecords.Which method of providing training data to Amazon SageMaker would meet the business requirements with the LEAST development overhead?Read More →

A machine learning specialist is running an Amazon SageMaker endpoint using the built-in object detection algorithm on a P3 instance for real-time predictions in a company’s production application.When evaluating the model’s resource utilization, the specialist notices that the model is using only a fraction of the GPU.Which architecture changes would ensure that provisioned resources are being utilized effectively?Read More →

A power company wants to forecast future energy consumption for its customers in residential properties and commercial business properties.Historical power consumption data for the last 10 years is available.A team of data scientists who performed the initial data analysis and feature selection will include the historical power consumption data and data such as weather, number of individuals on the property, and public holidays.The data scientists are using Amazon Forecast to generate the forecasts.Which algorithm in Forecast should the data scientists use to meet these requirements?Read More →