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NEW QUESTION 37
An agency collects census information within a country to determine healthcare and social program needs by province and city. The census form collects responses for approximately 500 questions from each citizen.
Which combination of algorithms would provide the appropriate insights? (Select TWO.)

A. The Latent Dirichlet Allocation (LDA) algorithmB. The principal component analysis (PCA) algorithmC. The Random Cut Forest (RCF) algorithmD. The k-means algorithmE. The factorization machines (FM) algorithm

Answer: B,D

Explanation:
The PCA and K-means algorithms are useful in collection of data using census form.

 

NEW QUESTION 38
You need to build classification workflows over several structured datasets currently stored in BigQuery. Because you will be performing the classification several times, you want to complete the following steps without writing code: exploratory data analysis, feature selection, model building, training, and hyperparameter tuning and serving. What should you do?

A. Run a BigQuery ML task to perform logistic regression for the classificationB. Use Al Platform to run the classification model job configured for hyperparameter tuningC. Use Al Platform Notebooks to run the classification model with pandas libraryD. Configure AutoML Tables to perform the classification task

Answer: D

Explanation:
https://cloud.google.com/automl-tables/docs/beginners-guide

 

NEW QUESTION 39
An online reseller has a large, multi-column dataset with one column missing 30% of its data. A Machine Learning Specialist believes that certain columns in the dataset could be used to reconstruct the missing data.
Which reconstruction approach should the Specialist use to preserve the integrity of the dataset?

A. Mean substitutionB. Multiple imputationC. Last observation carried forwardD. Listwise deletion

Answer: B

Explanation:
Explanation/Reference: https://worldwidescience.org/topicpages/i/imputing+missing+values.html

 

NEW QUESTION 40
You are an ML engineer at an ecommerce company and have been tasked with building a model that predicts how much inventory the logistics team should order each month. Which approach should you take?

A. Use a regression model to predict how much additional inventory should be purchased each month. Give the results to the logistics team at the beginning of the month so they can increase inventory by the amount predicted by the model.B. Use a classification model to classify inventory levels as UNDER_STOCKED, OVER_STOCKED, and CORRECTLY_STOCKED. Give the report to the logistics team each month so they can fine-tune inventory levels.C. Use a clustering algorithm to group popular items together. Give the list to the logistics team so they can increase inventory of the popular items.D. Use a time series forecasting model to predict each item's monthly sales. Give the results to the logistics team so they can base inventory on the amount predicted by the model.

Answer: A

 

NEW QUESTION 41
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