Top 10 Artificial Intelligence Interview Questions & Answers

What is Artificial Intelligence?

Artificial Intelligence (AI) is an area of computer science that emphasizes the creation of intelligent machines that work and react like humans.

What are the different domains of Artificial Intelligence?

Machine Learning Neural Networks Robotics Expert Systems Fuzzy Logic Systems Natural Language Processing

What are different platforms for Artificial Intelligence (AI) development?

1. Amazon AI services 2. Tensorflow 3. Google AI services 4. Microsoft Azure AI platform 5. Infosys Nia 6. IBM Watson 7. H2O 8. Polyaxon 9. PredictionIO

What are the programming languages used for Artificial Intelligence?

Python, LISP, Java, C++, R are some of the programming languages used for Artificial Intelligence.

What is Q-Learning?

The Q-learning is a Reinforcement Learning algorithm in which an agent tries to learn the optimal policy from its past experiences with the environment.

What is Deep Learning?

Deep learning imitates the way our brain works i.e. it learns from experiences. It uses the concepts of neural networks to solve complex problems.

What are Bayesian Networks?

A Bayesian network is a statistical model that represents a set of variables and their conditional dependencies in the form of a directed acyclic graph.

What are the different components of NLP?

Natural Language Understanding includes: – Mapping input to useful representations – Analyzing different aspects of the language Natural Language Generation includes: – Text Planning – Sentence Planning – Text Realization

How is Computer Vision and AI related?

Computer Vision is a field of Artificial Intelligence that is used to obtain information from images or multi-dimensional data. Machine Learning algorithms such as K-means is used for Image Segmentation, Support Vector Machine is used for Image Classification and so on.

How can AI be used in detecting fraud?

Artificial Intelligence is used in Fraud detection problems by implementing Machine Learning algorithms for detecting anomalies and studying hidden patterns in data.

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