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Artificial Intelligence Interview Questions
Questions Answers Views Company eMail

Explain the term "data warehouse".

322

What do you understand by ensemble learning?

314

What do you understand by confusion matrix?

321

What do you understand by the term data science?

308

What do you understand by normal distribution?

442

Do you prefer python or r for text analytics?

280

Why is resampling done?

286

What is overfitting?

422

Where to seek help in case of discrepancies in tableau?

529

What are the feature vectors?

284

What do you understand by the selection bias? What are its various types?

285

What is selection bias and why does it matter?

295

What are numpy, scipy, and spark essential datatypes?

353

why is data cleaning important for analysis?

319

Can you compare the validation set with the test set?

294


Un-Answered Questions { Artificial Intelligence }

How can you handle duplicate values in a dataset for a variable in Python?

228


What are confounding variables?

128


Describe a real-world use case of Edge AI.

62


What is the role of education in preparing society for widespread AI adoption?

1


What is artificial intelligence?

872


Explain how to use dmx-the data mining query language?

21


What is the batch in machine learning?

110


What is pragmatics nlp terminology?

805


Explain Examples of Data Science?

290


What is pruning in decision trees?

107


Tell us what evaluation approaches would you work to gauge the effectiveness of a machine learning model?

70


Explain false negative, false positive, true negative and true positive with a simple example?

88


How do generative adversarial networks (GANs) work?

28


What is calibration in machine learning?

98


Which are the two components of bayesian logic program?

65