Machine Learning Specialty (Page 5)

A data scientist at a financial services company used Amazon SageMaker to train and deploy a model that predicts loan defaults.The model analyzes new loan applications and predicts the risk of loan default.To train the model, the data scientist manually extracted loan data from a database.The data scientist performed the model training and deployment steps in a Jupyter notebook that is hosted on SageMaker Studio notebooks.The model’s prediction accuracy is decreasing over time.Which combination of steps is the MOST operationally efficient way for the data scientist to maintain the model’s accuracy? (Choose two.)Read More →

An online advertising company is developing a linear model to predict the bid price of advertisements in real time with low-latency predictions.A data scientist has trained the linear model by using many features, but the model is overfitting the training dataset.The data scientist needs to prevent overfitting and must reduce the number of features.Which solution will meet these requirements?Read More →

A credit card company wants to identify fraudulent transactions in real time.A data scientist builds a machine learning model for this purpose.The transactional data is captured and stored in Amazon S3.The historic data is already labeled with two classes: fraud (positive) and fair transactions (negative).The data scientist removes all the missing data and builds a classifier by using the XGBoost algorithm in Amazon SageMaker.The model produces the following results:• True positive rate (TPR): 0.700• False negative rate (FNR): 0.300• True negative rate (TNR): 0.977• False positive rate (FPR): 0.023• Overall accuracy: 0.949Which solution should the data scientist use to improve the performance of the model?Read More →

Each morning, a data scientist at a rental car company creates insights about the previous day’s rental car reservation demands.The company needs to automate this process by streaming the data to Amazon S3 in near real time.The solution must detect high-demand rental cars at each of the company’s locations.The solution also must create a visualization dashboard that automatically refreshes with the most recent data.Which solution will meet these requirements with the LEAST development time?Read More →

A manufacturing company wants to create a machine learning (ML) model to predict when equipment is likely to fail.A data science team already constructed a deep learning model by using TensorFlow and a custom Python script in a local environment.The company wants to use Amazon SageMaker to train the model.Which TensorFlow estimator configuration will train the model MOST cost-effectively?Read More →

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?Read More →

A Machine Learning Specialist is creating a new natural language processing application that processes a dataset comprised of 1 million sentences.The aim is to then run Word2Vec to generate embeddings of the sentences and enable different types of predictions.Here is an example from the dataset:”The quck BROWN FOX jumps over the lazy dog.`Which of the following are the operations the Specialist needs to perform to correctly sanitize and prepare the data in a repeatable manner? (Choose three.)Read More →

A monitoring service generates 1 TB of scale metrics record data every minute.A Research team performs queries on this data using Amazon Athena.The queries run slowly due to the large volume of data, and the team requires better performance.How should the records be stored in Amazon S3 to improve query performance?Read More →

A Machine Learning Specialist working for an online fashion company wants to build a data ingestion solution for the company’s Amazon S3-based data lake.The Specialist wants to create a set of ingestion mechanisms that will enable future capabilities comprised of:✑ Real-time analytics✑ Interactive analytics of historical data✑ Clickstream analytics✑ Product recommendationsWhich services should the Specialist use?Read More →

A Data Science team within a large company uses Amazon SageMaker notebooks to access data stored in Amazon S3 buckets.The IT Security team is concerned that internet-enabled notebook instances create a security vulnerability where malicious code running on the instances could compromise data privacy.The company mandates that all instances stay within a secured VPC with no internet access, and data communication traffic must stay within the AWS network.How should the Data Science team configure the notebook instance placement to meet these requirements?Read More →