(Oct-2023) Latest AIP-210 Dumps for Success in Actual CertNexus Certified [Q15-Q39]

NO.15 Which of the following can benefit from deploying a deep learning model as an embedded model on edge devices?

NO.16 Which type of regression represents the following formula: y = c + b*x, where y = estimated dependent variable score, c = constant, b = regression coefficient, and x = score on the independent variable?

NO.17 An AI practitioner incorporates risk considerations into a deployment plan and decides to log and store historical predictions for potential, future access requests.
Which ethical principle is this an example of?

NO.18 Which of the following metrics is being captured when performing principal component analysis?

NO.19 When working with textual data and trying to classify text into different languages, which approach to representing features makes the most sense?

NO.20 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?

NO.21 Normalization is the transformation of features:

NO.22 When should the model be retrained in the ML pipeline?

NO.23 Which of the following algorithms is an example of unsupervised learning?

NO.24 A healthcare company experiences a cyberattack, where the hackers were able to reverse-engineer a dataset to break confidentiality.
Which of the following is TRUE regarding the dataset parameters?

NO.25 In addition to understanding model performance, what does continuous monitoring of bias and variance help ML engineers to do?

NO.26 Which of the following is the primary purpose of hyperparameter optimization?

NO.27 A change in the relationship between the target variable and input features is

NO.28 Word Embedding describes a task in natural language processing (NLP) where:

NO.29 Which of the following unsupervised learning models can a bank use for fraud detection?

NO.30 Which of the following describes a typical use case of video tracking?

NO.31 A data scientist is tasked to extract business intelligence from primary data captured from the public. Which of the following is the most important aspect that the scientist cannot forget to include?

NO.32 You have a dataset with many features that you are using to classify a dependent variable. Because the sample size is small, you are worried about overfitting. Which algorithm is ideal to prevent overfitting?

NO.33 Which of the following is a privacy-focused law that an AI practitioner should adhere to while designing and adapting an AI system that utilizes personal data?

NO.34 Which of the following equations best represent an LI norm?

NO.35 The following confusion matrix is produced when a classifier is used to predict labels on a test dataset. How precise is the classifier?

NO.36 Which two of the following criteria are essential for machine learning models to achieve before deployment?
(Select two.)

NO.37 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?

NO.38 Which two encodes can be used to transform categories data into numerical features? (Select two.)

NO.39 In which of the following scenarios is lasso regression preferable over ridge regression?