Artificial Intelligence Interview Questions – Set 09

Give an explanation on the difference between strong AI and weak AI? Strong AI makes strong claims that computers can be made to think on a level equal to humans while weak AI simply predicts that some features that are resembling to human intelligence can be incorporated to computer to make it more useful tools. … Read more

Artificial Intelligence Interview Questions – Set 08

How would you go about choosing an algorithm to solve a business problem? First, you have to develop a “problem statement” that’s based on the problem provided by the business. This step is essential because it’ll help ensure that you fully understand the type of problem and the input and the output of the problem … Read more

Artificial Intelligence Interview Questions – Set 07

What are the different algorithm techniques you can use in AI and ML? Some algorithm techniques that can be leveraged are: Learning to learn Reinforcement learning (deep adversarial networks, q-learning, and temporal difference) Semi-supervised learning Supervised learning (decision trees, linear regression, naive bayes, nearest neighbor, neural networks, and support vector machines) Transduction Unsupervised learning (association … Read more

Artificial Intelligence Interview Questions – Set 06

What is an expert system? What are the characteristics of an expert system? An expert system is an Artificial Intelligence program that has expert-level knowledge about a specific area and how to utilize its information to react appropriately. These systems have the expertise to substitute a human expert. Their characteristics include: High performance Adequate response … Read more

Artificial Intelligence Interview Questions – Set 05

List the programming languages used in AI. Python R Lisp Prolog Java What’s an eigenvalue? What about an eigenvector? The directions along which a particular linear transformation compresses, flips, or stretches is called eigenvalue. Eigenvectors are used to understand these linear transformations. For example, to make better sense of the covariance of the covariance matrix, … Read more