Artificial Intelligence Interview Questions, Answers for Freshers and Experienced asked in various Company Job Interviews

AI Algorithms (74)
AI Natural Language Processing (96)
AI Knowledge Representation Reasoning (12)
AI Robotics (183)

Artificial Intelligence Interview Questions

Questions Answers Views Company eMail

How will you explain machine learning into a layperson?

What do you mean by parametric models? Also, give some examples of them?

Why do we convert categorical variables into factor?

104

What type of learning is needed when the system needs to adapt to rapidly changing data?

124

How to decide one problem is a machine learning problem or not?

194

What is the sigmoid function in machine learning?

114

Give a drawback of gradient descent ?

Logistic regression gives probabilities as a result then how do we use it to predict a binary outcome?

What is adagrad algorithm in machine learning?

106

What kind of problems lend themselves to machine learning?

What is the difference between supervised and unsupervised learning?

Which one would you prefer to choose – model accuracy or model performance?

185

What are standardization and normalisation?

107

What is bias-variance trade-off in machine learning?

Does 100% precision mean that our model predicts all the values correctly?

Un-Answered Questions { Artificial Intelligence }

Differentiate between data modeling and database design?

329

Which gpu is best for deep learning?

What challenges do AI systems face in finance regarding data privacy?

What are the factors used to produce "People You May Know" data product on LinkedIn?

315

What industries benefit most from explainable AI?

How would you address fairness in AI for multi-lingual or global applications?

How do you handle setbacks in AI research and development?

Can you discuss the impact of AI on the job market in these sectors?

Tell us an example where ensemble techniques might be useful?

What jupyter used?

310

Distinguish between strong and weak artificial intelligence?

856

What is the way of dealing with “exploding gradient” problem in rnns?answer: gradient clipping, the gradient is set to the threshold. Gradient clipping will chop the gradients or restricts them to a threshold value to prevent the gradients from getting too large.

903

What challenges do AI-powered education systems face?

102

What types of motors used in industrial robots?

861

Give some situations where you will use an SVM over a RandomForest Machine Learning algorithm and vice-versa?

460

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