Passing CertNexus AIP-210 Exam Using 2023 Practice Tests [Q20-Q42]

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Passing CertNexus AIP-210 Exam Using 2023 Practice Tests

AIP-210 Study Guide Brilliant AIP-210 Exam Dumps PDF

Q20. Which of the following equations best represent an LI norm?

|x| + |y|

|x|+|y|^2

|x|-|y|

|x|^2+|y|^2

Q21. When should the model be retrained in the ML pipeline?

A new monitoring component is added.

Concept drift is detected in the pipeline.

More data become available for the training phase.

Some outliers are detected in live data.

Q22. Which of the following is TRUE about SVM models?

They can be used only for classification.

They can be used only for regression.

They can take the feature space into higher dimensions to solve the problem.

They use the sigmoid function to classify the data points.

Q23. Workflow design patterns for the machine learning pipelines:

Aim to explain how the machine learning model works.

Represent a pipeline with directed acyclic graph (DAG).

Seek to simplify the management of machine learning features.

Separate inputs from features.

Q24. A company is developing a merchandise sales application The product team uses training data to teach the AI model predicting sales, and discovers emergent bias. What caused the biased results?

The AI model was trained in winter and applied in summer.

The application was migrated from on-premise to a public cloud.

The team set flawed expectations when training the model.

The training data used was inaccurate.

Q25. When should you use semi-supervised learning? (Select two.)

A small set of labeled data is available but not representative of the entire distribution.

A small set of labeled data is biased toward one class.

Labeling data is challenging and expensive.

There is a large amount of labeled data to be used for predictions.

There is a large amount of unlabeled data to be used for predictions.

Q26. Which of the following can take a question in natural language and return a precise answer to the question?

Databricks

IBM Watson

Pandas

Spark ML

Q27. Which of the following describes a benefit of machine learning for solving business problems?

Increasing the quantity of original data

Increasing the speed of analysis

Improving the constraint of the problem

Improving the quality of original data

Q28. Which of the following is the primary purpose of hyperparameter optimization?

Controls the learning process of a given algorithm

Makes models easier to explain to business stakeholders

Improves model interpretability

Increases recall over precision

Q29. Which of the following is a common negative side effect of not using regularization?

Overfitting

Slow convergence time

Higher compute resources

Low test accuracy

Q30. A dataset can contain a range of values that depict a certain characteristic, such as grades on tests in a class during the semester. A specific student has so far received the following grades: 76,81, 78, 87, 75, and 72.
There is one final test in the semester. What minimum grade would the student need to achieve on the last test to get an 80% average?

Q31. 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?

Cyberprotection

Cybersecurity

Data privacy

Data security

Q32. In a self-driving car company, ML engineers want to develop a model for dynamic pathing. Which of following approaches would be optimal for this task?

Dijkstra Algorithm

Reinforcement learning

Supervised Learning.

Unsupervised Learning

Q33. Which of the following approaches is best if a limited portion of your training data is labeled?

Dimensionality reduction

Probabilistic clustering

Reinforcement learning

Semi-supervised learning

Q34. Which three security measures could be applied in different ML workflow stages to defend them against malicious activities? (Select three.)

Disable logging for model access.

Launch ML Instances In a virtual private cloud (VPC).

Monitor model degradation.

Use data encryption.

Use max privilege to control access to ML artifacts.

Use Secrets Manager to protect credentials.

Q35. 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?

A decision tree algorithm, because the problem is a classification problem with a small number of features.

k-means, because this is a clustering problem with a small number of features.

Logistic regression, because this is a classification problem and our data is linearly separable.

Neural network model, because this is a classification problem with a large number of features.

Q36. In addition to understanding model performance, what does continuous monitoring of bias and variance help ML engineers to do?

Detect hidden attacks

Prevent hidden attacks

Recover from hidden attacks

Respond to hidden attacks

Q37. Which of the following regressions will help when there is the existence of near-linear relationships among the independent variables (collinearity)?

Clustering

Linear regression

Polynomial regression

Ridge regression

Q38. Which of the following can benefit from deploying a deep learning model as an embedded model on edge devices?

A more complex model

Guaranteed availability of enough space

Increase in data bandwidth consumption

Reduction in latency

Q39. Which two of the following decrease technical debt in ML systems? (Select two.)

Boundary erosion

Design anti-patterns

Documentation readability

Model complexity

Refactoring

Q40. Which of the following statements are true regarding highly interpretable models? (Select two.)

They are usually binary classifiers.

They are usually easier to explain to business stakeholders.

They are usually referred to as “black box” models.

They are usually very good at solving non-linear problems.

They usually compromise on model accuracy for the sake of interpretability.

Q41. 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?

Lasso regression

Linear regression

Polynomial regression

Ridge regression

Q42. Which of the following text vectorization methods is appropriate and correctly defined for an English-to-Spanish translation machine?

Using TF-IDF because in translation machines, we do not care about the order of the words.

Using TF-IDF because in translation machines, we need to consider the order of the words.

Using Word2vec because in translation machines, we do not care about the order of the words.

Using Word2vec because in translation machines, we need to consider the order of the words.

CertNexus AIP-210 Exam Syllabus Topics:

Topic	Details
Topic 1	Transform numerical and categorical data Address business risks, ethical concerns, and related concepts in operationalizing the model
Topic 2	Design machine and deep learning models Explain data collection transformation process in ML workflow
Topic 3	Identify potential ethical concerns Analyze machine learning system use cases
Topic 4	Train, validate, and test data subsets Training and Tuning ML Systems and Models
Topic 5	Recognize relative impact of data quality and size to algorithms Engineering Features for Machine Learning

Free AIP-210 Test Questions Real Practice Test Questions: https://www.prepawaypdf.com/CertNexus/AIP-210-practice-exam-dumps.html

Passing CertNexus AIP-210 Exam Using 2023 Practice Tests [Q20-Q42]

CertNexus AIP-210 Exam Syllabus Topics:

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