Updated AIP-210 Exam Dumps (V9.03) – Improve Your Preparation and Pass AIP-210 Exam with Full Confidence

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?

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

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?

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?

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.)

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?

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

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

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

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?

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

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?

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?

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

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

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

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.)

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

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?

21. R-squared is a statistical measure that:

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

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

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

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

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

How precise is the classifier?

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?

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

29. 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?

30. 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?