An aircraft engine manufacturing company is measuring 200 performance metrics in a time-series. Engineers

want to detect critical manufacturing defects in near-real time during testing. All of the data needs to be stored

for offline analysis.

What approach would be the MOST effective to perform near-real time defect detection?

A Machine Learning Specialist is deciding between building a naive Bayesian model or a full Bayesian network

for a classification problem. The Specialist computes the Pearson correlation coefficients between each

feature and finds that their absolute values range between 0.1 to 0.95.

Which model describes the underlying data in this situation?

A Machine Learning Specialist prepared the following graph displaying the results of k-means for k = [1:10]

Considering the graph, what is a reasonable selection for the optimal choice of k?

A data science team is planning to build a natural language processing (NLP) application. The application's text preprocessing stage will include part-of-speech tagging and key phase extraction. The preprocessed text will be input to a custom classification algorithm that the data science team has already written and trained using Apache MXNet.

Which solution can the team build MOST quickly to meet these requirements?

A Marketing Manager at a pet insurance company plans to launch a targeted marketing campaign on social media to acquire new customers Currently, the company has the following data in Amazon Aurora

* Profiles for all past and existing customers

* Profiles for all past and existing insured pets

* Policy-level information

* Premiums received

* Claims paid

What steps should be taken to implement a machine learning model to identify potential new customers on social media?