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MLS-C01 - AWS Certified Machine Learning - Specialty

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MLS-C01 Questions and Answers

Question # 1

A real estate company wants to create a machine learning model for predicting housing prices based on a

historical dataset. The dataset contains 32 features.

Which model will meet the business requirement?


Logistic regression


Linear regression




Principal component analysis (PCA)

Question # 2

A company wants to detect credit card fraud. The company has observed that an average of 2% of credit card transactions are fraudulent. A data scientist trains a classifier on a year's worth of credit card transaction data. The classifier needs to identify the fraudulent transactions. The company wants to accurately capture as many fraudulent transactions as possible.

Which metrics should the data scientist use to optimize the classifier? (Select TWO.)




False positive rate




Fl score


True positive rate

Question # 3

An interactive online dictionary wants to add a widget that displays words used in similar contexts. A Machine Learning Specialist is asked to provide word features for the downstream nearest neighbor model powering the widget.

What should the Specialist do to meet these requirements?


Create one-hot word encoding vectors.


Produce a set of synonyms for every word using Amazon Mechanical Turk.


Create word embedding factors that store edit distance with every other word.


Download word embedding’s pre-trained on a large corpus.

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