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Artificial Intelligence Interview Questions
Questions Answers Views Company eMail

Compare and contrast CNNs and RNNs.

63

Imagine you're building a model for loan approvals. How do you make sure it doesn't discriminate?

65

How do you ensure that your models are fair and unbiased?

86

Describe different approaches to text-to-speech (TTS) synthesis?

86

Discuss the differences between Bayesian Networks and Markov Models.

82

How would you approach the design of an AI agent that is ethical by design?

67

What are some common NLP tasks?

91

What is the vanishing gradient problem in deep learning?

81

Explain the concept of backpropagation.

75

How do you deal with ambiguity in requirements when developing AI applications?

84

Describe different methods for model interpretability.

64

How can AI be used to improve weather prediction?

84

Describe a challenging AI project you worked on. What were the key learnings?

85

What is the relationship between AI and cognitive science?

86

How would you build a simple classification model?

79


Un-Answered Questions { Artificial Intelligence }

How can anomaly detection systems improve AI safety?

1


There are also other operators, more linguistic in nature, called __________ that can be applied to fuzzy set theory. a) Hedges b) Lingual Variable c) Fuzz Variable d) None of the mentioned

3005


What is jupyter ?

366


What are the various types of selection bias?

346


What is semantics natural language processing terminology?

841


How is ML different from artificial intelligence?

127


Why do you want to work as a data scientist?

305


Who is associated with the theory of symbolic learning?

80


Suppose 2 batsmen each on 94. 7 Runs to win in 3 balls. Both make unbeaten 100. How?

967


What are the benefits of AI in legal research?

79


Explain the Algorithm Technique of Supervised Learning in Machine Learning?

81


Discuss linear regression?

328


Can AI systems ever be completely free of bias? Why or why not?

1


What’s the trade-off between bias and variance?

111


How will you explain machine learning into a layperson?

67