A Machine Learning Specialist is building a convolutional neural network (CNN) that will classify 10 types of animals. The Specialist has built a series of layers in a neural network that will take an input image of an animal, pass it through a series of convolutional and pooling layers, and then finally pass it through a dense and fully connected layer with 10 nodes The Specialist would like to get an output from the neural network that is a probability distribution of how likely it is that the input image belongs to each of the 10 classes
Which function will produce the desired output?
An aircraft engine manufacturing company is measuring 200 performance metrics in a time-series. Engineers
want to detect critical manufacturing defects in near-real time during testing. All of the data needs to be stored
for offline analysis.
What approach would be the MOST effective to perform near-real time defect detection?
A data scientist uses Amazon SageMaker Data Wrangler to define and perform transformations and feature engineering on historical data. The data scientist saves the transformations to SageMaker Feature Store.
The historical data is periodically uploaded to an Amazon S3 bucket. The data scientist needs to transform the new historic data and add it to the online feature store The data scientist needs to prepare the .....historic data for training and inference by using native integrations.
Which solution will meet these requirements with the LEAST development effort?
An ecommerce company has observed that customers who use the company's website rarely view items that the website recommends to customers. The company wants to recommend items to customers that customers are more likely to want to purchase.
Which solution will meet this requirement in the SHORTEST amount of time?
A company stores its documents in Amazon S3 with no predefined product categories. A data scientist needs to build a machine learning model to categorize the documents for all the company's products.
Which solution will meet these requirements with the MOST operational efficiency?
A company wants to classify user behavior as either fraudulent or normal. Based on internal research, a Machine Learning Specialist would like to build a binary classifier based on two features: age of account and transaction month. The class distribution for these features is illustrated in the figure provided.
Based on this information which model would have the HIGHEST accuracy?
A financial services company wants to automate its loan approval process by building a machine learning (ML) model. Each loan data point contains credit history from a third-party data source and demographic information about the customer. Each loan approval prediction must come with a report that contains an explanation for why the customer was approved for a loan or was denied for a loan. The company will use Amazon SageMaker to build the model.
Which solution will meet these requirements with the LEAST development effort?
A company needs to quickly make sense of a large amount of data and gain insight from it. The data is in different formats, the schemas change frequently, and new data sources are added regularly. The company wants to use AWS services to explore multiple data sources, suggest schemas, and enrich and transform the data. The solution should require the least possible coding effort for the data flows and the least possible infrastructure management.
Which combination of AWS services will meet these requirements?