CertNexus Certified Artificial Intelligence Practitioner AIP-210 Exam Dumps Available

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CertNexus Certified Artificial Intelligence Practitioner AIP-210 exam information is available. There are 80 multiple-choice/Multiple-response questions in the real CertNexus AIP-210 exam, and you have 120 minutes to answer all the questions. AIP-210 exam can be taken at Pearson VUE test centers or online with Pearson OnVUE online proctoring. We have cracked the latest CertNexus Certification AIP-210 exam dumps, which are valuable in your preparation. Free CertNexus Certified Artificial Intelligence Practitioner AIP-210 exam dumps are below.

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1. You and your team need to process large datasets of images as fast as possible for a machine learning task. The project will also use a modular framework with extensible code and an active developer community.

Which of the following would BEST meet your needs?

Caffe

Keras

Microsoft Cognitive Services

TensorBoard

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

Avoiding mechanisms to explain and justify automated decisions.

Collecting and processing the largest amount of data possible.

Understanding, documenting, and displaying data lineage.

Utilizing quasi-identifiers and non-unique identifiers, alone or in combination.

3. 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

4. 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?

Deep neural network

K-nearest neighbors

Random forest

SVM

5. 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?

6. 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.

7. 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?

The model is overfitted and trained on a high quantity of patient records.

The model is overfitted and trained on a low quantity of patient records.

The model is underfitted and trained on a high quantity of patient records.

The model is underfitted and trained on a low quantity of patient records.

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

Bag of words model with TF-IDF

Bag of bigrams (2 letter pairs)

Word2Vec algorithm

Clustering similar words and representing words by group membership

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

As new resources become available

Once a month

When the input format changes

When the input volume changes

10. Which of the following tools would you use to create a natural language processing application?

AWS DeepRacer

Azure Search

DeepDream

NLTK

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11. A classifier has been implemented to predict whether or not someone has a specific type of disease.

Considering that only 1% of the population in the dataset has this disease, which measures will work the BEST to evaluate this model?

Mean squared error

Precision and accuracy

Precision and recall

Recall and explained variance

12. Which of the following describes a typical use case of video tracking?

Augmented dreaming

Medical diagnosis

Traffic monitoring

Video composition

13. 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?

Deep learning neural network

Random forest

Ridge regression

Support-vector machine

14. 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?

Equality of variance (Homoscedastidty)

Independence

Linearity

Normality

15. 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.

16. 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

17. Which of the following is the definition of accuracy?

(True Positives + False Positives) / Total Predictions

(True Positives + True Negatives) / Total Predictions

True Positives / (True Positives + False Negatives)

True Positives / (True Positives + False Positives)

18. Personal data should not be disclosed, made available, or otherwise used for purposes other than specified with which of the following exceptions? (Select two.)

If it is for a good cause.

If it was collected accidentally.

If it was requested by the authority of law.

If it was with consent of the person it is collected from.

If the data is only collected once.

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

Data as a Service (DaaS) can host the databases providing backups, clustering, and high availability.

Infrastructure as a Service (IaaS) can provide CPU, memory, disk, network and GP

Platform as a Service (PaaS) can provide some services within an application such as payment applications to create efficient results.

Software as a Service (SaaS) can provide AI practitioner data science services such as Jupyter notebooks.

20. 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

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21. R-squared is a statistical measure that:

Combines precision and recall of a classifier into a single metric by taking their harmonic mean.

Expresses the extent to which two variables are linearly related.

Is the proportion of the variance for a dependent variable thaf’ s explained by independent variables.

Represents the extent to which two random variables vary together.

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

|x| + |y|

|x|+|y|^2

|x|-|y|

|x|^2+|y|^2

23. 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.

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

Boundary erosion

Design anti-patterns

Documentation readability

Model complexity

Refactoring

25. Which of the following describes a neural network without an activation function?

A form of a linear regression

A form of a quantile regression

An unsupervised learning technique

A radial basis function kernel

26. The following confusion matrix is produced when a classifier is used to predict labels on a test dataset.

How precise is the classifier?

48/(48+37)

37/(37+8)

37/(37+7)

(48+37)/100

27. 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?

Delete entire rows that contain any missing features.

Fill in missing features with random values for that feature in the training set.

Fill in missing features with the average of observed values for that feature in the entire dataset.

Delete entire columns that contain any missing features.

CertNexus Certified Artificial Intelligence Practitioner AIP-210 Exam Dumps Available

CertNexus Certified Artificial Intelligence Practitioner AIP-210 Exam Dumps Available

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