Artificial Intelligence interview questions

Artificial Intelligence

16. How would you go about choosing an algorithm to solve a business problem?
Identify the actual problem or requirements of the problem. For example, here it is to identify how much is the drop rate from trial to un-paid users and identify why users are not converting.
Break the bigger problem into smaller sets, for example, here those are – whether the users are able to use your product as it’s meant to, are they even reaching to the product’s main features. The most important aspect of this is to identify the right audience as a single problem is meant for only a certain audience.
Decide the work plan for the first part of the problem. It can be anything from creating a login system to a single HTML page. Here only, the coding logic comes in.

17. Can you name the properties of a good knowledge representation system?
A good knowledge representation system must have properties such as: Representational Accuracy: It should represent all kinds of required knowledge. Inferential Adequacy: It should be able to manipulate the representational structures to produce new knowledge corresponding to the existing structure.

18. What’s regularization in AI?
Regularization is a technique used for tuning the function by adding an additional penalty term in the error function. The additional term controls the excessively fluctuating function such that the coefficients don’t take extreme values.

19. What is Prolog in AI?
Prolog, which is short for programming logic, is a programming language used in creating artificial intelligence. Prolog is classified as a logic programming language and relies on the user to specify the rules and facts about a situation along with the end goal, otherwise known as a query.

20. Mention the difference between statistical AI and Classical AI ?
Statistical AI, arising from machine learning, tends to be more concerned with “inductive” thought: given a set of patterns, induce the trend. Classical AI, on the other hand, is more concerned with “deductive” thought: given a set of constraints, deduce a conclusion. Another difference, as mentioned in the previous question, is that C++ tends to be a favourite language for statistical AI while LISP dominates in classical AI.
Image result for what is the difference between statistical AI and Classical AI ?Also , Machine learning is based on a number of earlier building blocks, starting with classical statistics. Statistics is just about the numbers and quantifying the data. There are many tools for finding relevant properties of the data but this is pretty close to pure mathematics.

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