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Artificial Intelligence Interview Questions
Questions Answers Views Company eMail

Explain p-value?

366

What is reinforcement learning?

338

Explain the term binomial probability formula?

323

When do you need to update the algorithm in data science?

333

Discuss 'naive' in a naive bayes algorithm?

352

Explain collaborative filtering

401

Define the term deep learning?

335

Explain the difference between data science and data analytics?

362

Explain the benefits of using statistics by data scientists

351

Define the term cross-validation

317

what the aim of conducting a/b testing?

332

What is the k-means clustering method?

376

Name various types of deep learning frameworks

439

State the difference between the expected value and mean value?

345

Explain auto-encoder

327


Un-Answered Questions { Artificial Intelligence }

Explain the Canny's Algorithm.

988


What are some emerging trends in multimodal AI?

78


What does linear in ‘linear regression’ actually mean?

178


What is artificial super intelligence?

908


What are the different dashboards in tensorflow?

1


Can you pick an algorithm. Write the psuedo-code for a parallel implementation?

908


Can you explain the concept of brain-inspired AI architectures and their applications?

85


Explain the Algorithm Technique of Transduction in Machine Learning?

101


Explain how cross-validation works and why it's important.

67


How can you import data in tensorflow ?

5


Tell us why is naïve bayes machine learning algorithm naïve?

1014


What is federated learning, and how does it relate to Edge AI?

81


Where was artificial intelligence invented?

921


Why are annotations used?

760


What is A/B testing in Machine Learning?

221