Amazon Exam MLS-C01 Topic 2 Question 94 Discussion

Actual exam question for Amazon's MLS-C01 exam

Question #: 94
Topic #: 2

A company is planning a marketing campaign to promote a new product to existing customers. The company has data (or 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.

...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%.

...should the company retrain the model to meet these requirements?

ASet the target_recall hyperparameter to 90% Set the binaryclassrfier model_selection_critena hyperparameter to recall_at_target_precision.

BSet the targetprecision hyperparameter to 90%. Set the binary classifier model selection criteria hyperparameter to precision at_jarget recall.

CUse 90% of the historical data for training Set the number of epochs to 20.

DSet the normalize_jabel hyperparameter to true. Set the number of classes to 2.

Show Suggested Answer

Suggested Answer: D

The best visualization for this task is to create a bar plot, faceted by year, of average sales for each region and add a horizontal line in each facet to represent average sales. This way, the data scientist can easily compare the yearly average sales for each region with the overall average sales and see the trends over time. The bar plot also allows the data scientist to see the relative performance of each region within each year and across years. The other options are less effective because they either do not show the yearly trends, do not show the overall average sales, or do not group the data by region.

References:

pandas.DataFrame.groupby --- pandas 2.1.4 documentation

pandas.DataFrame.plot.bar --- pandas 2.1.4 documentation

Matplotlib - Bar Plot - Online Tutorials Library

by Dorathy at Jun 03, 2024, 04:36 PM

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Bette

21 days ago

I'm torn between options A and B. Maybe I should just flip a coin and hope for the best. Or maybe I should just ask the AI assistant to make the decision for me. It's not like I'm paying attention anyway.

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Yuki

3 days ago

I think you should go with option A. It seems like the best choice based on the requirements.

upvoted 0 times

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Sunshine

30 days ago

Setting the normalize_label hyperparameter to true and the number of classes to 2 seems like a strange solution. I don't think that's going to help with the recall and precision requirements.

upvoted 0 times

Lindsay

2 days ago

A: A) Set the target_recall hyperparameter to 90% Set the binaryclassrfier model_selection_critena hyperparameter to recall_at_target_precision.

upvoted 0 times

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Mertie

1 months ago

Using 90% of the historical data for training and setting the number of epochs to 20 doesn't sound right to me. Shouldn't we be focusing on the model's performance metrics?

upvoted 0 times