Machine Learning Specialty (Page 29)

A company uses a long short-term memory (LSTM) model to evaluate the risk factors of a particular energy sector.The model reviews multi-page text documents to analyze each sentence of the text and categorize it as either a potential risk or no risk.The model is not performing well, even though the Data Scientist has experimented with many different network structures and tuned the corresponding hyperparameters.Which approach will provide the MAXIMUM performance boost?Read More →

A trucking company is collecting live image data from its fleet of trucks across the globe.The data is growing rapidly and approximately 100 GB of new data is generated every day.The company wants to explore machine learning uses cases while ensuring the data is only accessible to specific IAM users.Which storage option provides the most processing flexibility and will allow access control with IAM?Read More →

A credit card company wants to build a credit scoring model to help predict whether a new credit card applicant will default on a credit card payment.The company has collected data from a large number of sources with thousands of raw attributes.Early experiments to train a classification model revealed that many attributes are highly correlated, the large number of features slows down the training speed significantly, and that there are some overfitting issues.The Data Scientist on this project would like to speed up the model training time without losing a lot of information from the original dataset.Which feature engineering technique should the Data Scientist use to meet the objectives?Read More →

A Machine Learning Specialist previously trained a logistic regression model using scikit-learn on a local machine, and the Specialist now wants to deploy it to production for inference only.What steps should be taken to ensure Amazon SageMaker can host a model that was trained locally?Read More →

A machine learning specialist works for a fruit processing company and needs to build a system that categorizes apples into three types.The specialist has collected a dataset that contains 150 images for each type of apple and applied transfer learning on a neural network that was pretrained on ImageNet with this dataset.The company requires at least 85% accuracy to make use of the model.After an exhaustive grid search, the optimal hyperparameters produced the following:✑ 68% accuracy on the training set✑ 67% accuracy on the validation setWhat can the machine learning specialist do to improve the system’s accuracy?Read More →

A company wants to create a data repository in the AWS Cloud for machine learning (ML) projects.The company wants to use AWS to perform complete ML lifecycles and wants to use Amazon S3 for the data storage.All of the company’s data currently resides on premises and is 40 ׀¢׀’ in size.The company wants a solution that can transfer and automatically update data between the on-premises object storage and Amazon S3.The solution must support encryption, scheduling, monitoring, and data integrity validation.Which solution meets these requirements?Read More →

A company is building a predictive maintenance model for its warehouse equipment.The model must predict the probability of failure of all machines in the warehouse.The company has collected 10,000 event samples within 3 months.The event samples include 100 failure cases that are evenly distributed across 50 different machine types.How should the company prepare the data for the model to improve the model’s accuracy?Read More →

A company operates an amusement park.The company wants to collect, monitor, and store real-time traffic data at several park entrances by using strategically placed cameras.The company’s security team must be able to immediately access the data for viewing.Stored data must be indexed and must be accessible to the company’s data science team.Which solution will meet these requirements MOST cost-effectively?Read More →

A company is planning a marketing campaign to promote a new product to existing customers.The company has data for past promotions that are similar.The company decides to try an experiment to send a more expensive marketing package to a smaller number of customers.The company wants to target the marketing campaign to customers who are most likely to buy the new product.The experiment requires that at least 90% of the customers who are likely to purchase the new product receive the marketing materials.The company trains a model by using the linear learner algorithm in Amazon SageMaker.The model has a recall score of 80% and a precision of 75%.How should the company retrain the model to meet these requirements?Read More →

A manufacturing company has a production line with sensors that collect hundreds of quality metrics.The company has stored sensor data and manual inspection results in a data lake for several months.To automate quality control, the machine learning team must build an automated mechanism that determines whether the produced goods are good quality, replacement market quality, or scrap quality based on the manual inspection results.Which modeling approach will deliver the MOST accurate prediction of product quality?Read More →