Deal of The Day! Hurry Up, Grab the Special Discount - Save 25% - Ends In 00:00:00 Coupon code: SAVE25
Welcome to Pass4Success

- Free Preparation Discussions

Amazon Exam MLS-C01 Topic 2 Question 94 Discussion

Actual exam question for Amazon's MLS-C01 exam
Question #: 94
Topic #: 2
[All MLS-C01 Questions]

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?

Show Suggested Answer Hide 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


Contribute your Thoughts:

Mertie
2 days 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
...
Sharen
8 days ago
I'm not sure about setting the target_recall to 90%. Wouldn't it be better to set the target_precision to 90% instead? Let me think about this...
upvoted 0 times
...
Brandon
13 days ago
Hmm, the model needs to have a recall of at least 90% to meet the requirements. Option A seems like the right choice here.
upvoted 0 times
...
Sean
19 days ago
I'm not sure. Maybe setting the targetprecision hyperparameter to 90% could also work.
upvoted 0 times
...
Florinda
20 days ago
I agree with Renea. Setting the target_recall hyperparameter to 90% seems like a good option.
upvoted 0 times
...
Renea
24 days ago
I think the company should retrain the model to meet the requirements.
upvoted 0 times
...

Save Cancel
az-700  pass4success  az-104  200-301  200-201  cissp  350-401  350-201  350-501  350-601  350-801  350-901  az-720  az-305  pl-300  

Warning: Cannot modify header information - headers already sent by (output started at /pass.php:70) in /pass.php on line 77