MLS-C01 (Page 17)

A Machine Learning Specialist needs to be able to ingest streaming data and store it in Apache Parquet files for exploration and analysis.Which of the following services would both ingest and store this data in the correct format?Read More →

A data scientist has explored and sanitized a dataset in preparation for the modeling phase of a supervised learning task.The statistical dispersion can vary widely between features, sometimes by several orders of magnitude.Before moving on to the modeling phase, the data scientist wants to ensure that the prediction performance on the production data is as accurate as possible.Which sequence of steps should the data scientist take to meet these requirements?Read More →

An online retailer collects the following data on customer orders: demographics, behaviors, location, shipment progress, and delivery time.A data scientist joins all the collected datasets.The result is a single dataset that includes 980 variables.The data scientist must develop a machine learning (ML) model to identify groups of customers who are likely to respond to a marketing campaign.Which combination of algorithms should the data scientist use to meet this requirement? (Choose two.)Read More →

A Marketing Manager at a pet insurance company plans to launch a targeted marketing campaign on social media to acquire new customers.Currently, the company has the following data in Amazon Aurora:✑ Profiles for all past and existing customers✑ Profiles for all past and existing insured pets✑ Policy-level information✑ Premiums received✑ Claims paidWhat steps should be taken to implement a machine learning model to identify potential new customers on social media?Read More →

A Machine Learning team uses Amazon SageMaker to train an Apache MXNet handwritten digit classifier model using a research dataset.The team wants to receive a notification when the model is overfitting.Auditors want to view the Amazon SageMaker log activity report to ensure there are no unauthorized API calls.What should the Machine Learning team do to address the requirements with the least amount of code and fewest steps?Read More →

A company has 2,000 retail stores.The company needs to develop a new model to predict demand based on holidays and weather conditions.The model must predict demand in each geographic area where the retail stores are located.Before deploying the newly developed model, the company wants to test the model for 2 to 3 days.The model needs to be robust enough to adapt to supply chain and retail store requirements.Which combination of steps should the company take to meet these requirements with the LEAST operational overhead? (Choose two.)Read More →

A data scientist needs to create a model for predictive maintenance.The model will be based on historical data to identify rare anomalies in the data.The historical data is stored in an Amazon S3 bucket.The data scientist needs to use Amazon SageMaker Data Wrangler to ingest the data.The data scientist also needs to perform exploratory data analysis (EDA) to understand the statistical properties of the data.Which solution will meet these requirements with the LEAST amount of compute resources?Read More →

A finance company has collected stock return data for 5,000 publicly traded companies.A financial analyst has a dataset that contains 2,000 attributes for each company.The financial analyst wants to use Amazon SageMaker to identify the top 15 attributes that are most valuable to predict future stock returns.Which solution will meet these requirements with the LEAST operational overhead?Read More →

A data scientist needs to develop a model to detect fraud.The data scientist has less data for fraudulent transactions than for legitimate transactions.The data scientist needs to check for bias in the model before finalizing the model.The data scientist needs to develop the model quickly.Which solution will meet these requirements with the LEAST operational overhead?Read More →

A business to business (B2B) ecommerce company wants to develop a fair and equitable risk mitigation strategy to reject potentially fraudulent transactions.The company wants to reject fraudulent transactions despite the possibility of losing some profitable transactions or customers.Which solution will meet these requirements with the LEAST operational effort?Read More →