EMT Practice Test

1. Question Content...

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Question1: You train a neural network model with two layers, each layer having four nodes, and realize that the model is underfit. Which of the actions below will NOT work to fix this underfitting?

Question2: Which of the following unsupervised learning models can a bank use for fraud detection?

Question3: In general, models that perform their tasks:

Question4: Which of the following regressions will help when there is the existence of near-linear relationships among the independent variables (collinearity)?

Question5: Which of the following can take a question in natural language and return a precise answer to the question?

Question6: We are using the k-nearest neighbors algorithm to classify the new data points. The features are on different scales.
Which method can help us to solve this problem?

Question7: Which of the following principles supports building an ML system with a Privacy by Design methodology?

Question8: The following confusion matrix is produced when a classifier is used to predict labels on a test dataset. How precise is the classifier?

Question9: For a particular classification problem, you are tasked with determining the best algorithm among SVM, random forest, K-nearest neighbors, and a deep neural network. Each of the algorithms has similar accuracy on your data. The stakeholders indicate that they need a model that can convey each feature's relative contribution to the model's accuracy. Which is the best algorithm for this use case?

Question10: Workflow design patterns for the machine learning pipelines:

Question11: You are implementing a support-vector machine on your data, and a colleague suggests you use a polynomial kernel. In what situation might this help improve the prediction of your model?

Question12: Your dependent variable Y is a count, ranging from 0 to infinity. Because Y is approximately log-normally distributed, you decide to log-transform the data prior to performing a linear regression.
What should you do before log-transforming Y?

Question13: Which of the following is the primary purpose of hyperparameter optimization?

Question14: In general, models that perform their tasks:

Question15: Why do data skews happen in the ML pipeline?

Question16: Which of the following items should be included in a handover to the end user to enable them to use and run a trained model on their own system? (Select three.)

Question17: Which database is designed to better anticipate and avoid risks of AI systems causing safety, fairness, or other ethical problems?

Question18: You are developing a prediction model. Your team indicates they need an algorithm that is fast and requires low memory and low processing power. Assuming the following algorithms have similar accuracy on your data, which is most likely to be an ideal choice for the job?

Question19: Your dependent variable data is a proportion. The observed range of your data is 0.01 to 0.99. The instrument used to generate the dependent variable data is known to generate low quality data for values close to 0 and close to 1. A colleague suggests performing a logit-transformation on the data prior to performing a linear regression. Which of the following is a concern with this approach?
Definition of logit-transformation
If p is the proportion: logit(p)=log(p/(l-p))

Question20: For each of the last 10 years, your team has been collecting data from a group of subjects, including their age and numerous biomarkers collected from blood samples. You are tasked with creating a prediction model of age using the biomarkers as input. You start by performing a linear regression using all of the data over the
10-year period, with age as the dependent variable and the biomarkers as predictors.
Which assumption of linear regression is being violated?

Question21: In addition to understanding model performance, what does continuous monitoring of bias and variance help ML engineers to do?

Question22: Which of the following options is a correct approach for scheduling model retraining in a weather prediction application?

Question23: You create a prediction model with 96% accuracy. While the model's true positive rate (TPR) is performing well at 99%, the true negative rate (TNR) is only 50%. Your supervisor tells you that the TNR needs to be higher, even if it decreases the TPR. Upon further inspection, you notice that the vast majority of your data is truly positive.
What method could help address your issue?

Question24: Which of the following pieces of AI technology provides the ability to create fake videos?

Question25: R-squared is a statistical measure that:

Question26: You have a dataset with thousands of features, all of which are categorical. Using these features as predictors, you are tasked with creating a prediction model to accurately predict the value of a continuous dependent variable. Which of the following would be appropriate algorithms to use? (Select two.)

Question27: Which two of the following criteria are essential for machine learning models to achieve before deployment?
(Select two.)

Question28: What is Word2vec?

Question29: Which of the following sentences is TRUE about the definition of cloud models for machine learning pipelines?

Question30: Which of the following statements are true regarding highly interpretable models? (Select two.)

Question31: Which of the following describes a neural network without an activation function?

Question32: Which of the following is a type 1 error in statistical hypothesis testing?

Question33: Which of the following metrics is being captured when performing principal component analysis?

Question34: When working with textual data and trying to classify text into different languages, which approach to representing features makes the most sense?

Question35: Which of the following is a common negative side effect of not using regularization?

Question36: Which of the following best describes distributed artificial intelligence?

Question37: An AI system recommends New Year's resolutions. It has an ML pipeline without monitoring components.
What retraining strategy would be BEST for this pipeline?

Question38: An organization sells house security cameras and has asked their data scientists to implement a model to detect human feces, as distinguished from animals, so they can alert th customers only when a human gets close to their house.
Which of the following algorithms is an appropriate option with a correct reason?

Question39: Which of the following sentences is true about model evaluation and model validation in ML pipelines?

Question40: Given a feature set with rows that contain missing continuous values, and assuming the data is normally distributed, what is the best way to fill in these missing features?

Question41: Which two techniques are used to build personas in the ML development lifecycle? (Select two.)

Question42: Which of the following are true about the transform-design pattern for a machine learning pipeline? (Select three.) It aims to separate inputs from features.