Question 1

For the given confusion matrix, what is the recall and precision of the model?

Options :

A : Recall = 0.92 Precision = 0.84

B : Recall = 0.84 Precision = 0.8

C : Recall = 0.92 Precision = 0.8

D : Recall = 0.8 Precision = 0.92

Answer: C

Question 2

A company is setting up an Amazon SageMaker environment. The corporate data security policy does not allow communication over the internet. How can the company enable the Amazon SageMaker service without enabling direct internet access to Amazon SageMaker notebook instances?

Options :

A : Create a NAT gateway within the corporate VPC.

B : Route Amazon SageMaker traffic through an on-premises network.

C : Create Amazon SageMaker VPC interface endpoints within the corporate VPC.

D : Create VPC peering with Amazon VPC hosting Amazon SageMaker.

Answer: C

Question 3

A machine learning specialist is developing a regression model to predict rental rates from rental listings. A variable named Wall_Color represents the most prominent exterior wall color of the property. The following is the sample data, excluding all other variables:

The specialist chose a model that needs numerical input data.

Which feature engineering approaches should the specialist use to allow the regression model to learn from the Wall_Color data? (Choose two.)

Options :

A : Apply integer transformation and set Red = 1, White = 5, and Green = 10.

B : Add new columns that store one-hot representation of colors.

C : Replace the color name string by its length.

D : Create three columns to encode the color in RGB format.

E : Replace each color name by its training set frequency.

Answer: B,D

Question 4

A machine learning (ML) specialist must develop a classification model for a financial services company. A domain expert provides the dataset, which is tabular with 10,000 rows and 1,020 features. During exploratory data analysis, the specialist finds no missing values and a small percentage of duplicate rows. There are correlation scores of > 0.9 for 200 feature pairs. The mean value of each feature is similar to its 50th percentile.

Which feature engineering strategy should the ML specialist use with Amazon SageMaker?

Options :

A : Apply dimensionality reduction by using the principal component analysis (PCA) algorithm.

B : Drop the features with low correlation scores by using a Jupyter notebook.

C : Apply anomaly detection by using the Random Cut Forest (RCF) algorithm.

D : Concatenate the features with high correlation scores by using a Jupyter notebook.

Answer: A

Question 5

An insurance company developed a new experimental machine learning (ML) model to replace an existing model that is in production. The company must validate the quality of predictions from the new experimental model in a production environment before the company uses the new experimental model to serve general user requests. Which one model can serve user requests at a time. The company must measure the performance of the new experimental model without affecting the current live traffic Which solution will meet these requirements?

Options :

A : A/B testing

B : Canary release

C : Shadow deployment

D : Blue/green deployment

Answer: C

Free MLS-C01 Mock Exam – Practice Online Confidently

Buying Options: