Overview

Question 1

What is Artificial Intelligence (AI)?

Answer 1

The creation of intelligent machines that react like humans, including fields like computer vision, data mining, machine learning, and deep learning.

Question 2

Define data, information, knowledge, and understanding.

Answer 2

Data: Symbols or raw facts.

Information: Processed data answering “who,” “what,” “where,” “when.”

Knowledge: Application of data/information, answering “how.”

Understanding: Appreciation of “why.”

Question 3

What is weak/narrow AI?

Answer 3

AI designed for specific tasks, with no self-awareness or understanding beyond its domain. Examples include Siri, Alexa, and chess AI.

Question 4

What is strong AI (AGI)?

Answer 4

A hypothetical AI capable of human-like reasoning, learning, and adapting to new situations without extra training. Not yet achieved.

Question 5

What is data mining?

Answer 5

The extraction of interesting, non-trivial, and useful patterns or knowledge from large datasets. It is also known as knowledge discovery, data archeology, or information harvesting.

Question 6

How does machine learning differ from data mining?

Answer 6

Machine Learning: Focuses on teaching computers to learn patterns from data to make predictions.

Data Mining: Focuses on identifying previously unknown patterns or anomalies in data for solving problems.

Question 7

Name some types of data used in data mining.

Answer 7

Data streams, time-series data, spatial data, multimedia databases, text databases, images/videos, and more.

Question 8

What are the two main types of supervised learning?

Answer 8

Classification: Categorizing data into labels.

Regression: Predicting continuous values.

Question 9

List common deep learning models.

Answer 9

Deep Neural Networks (DNN)

Convolutional Neural Networks (CNN)

Recurrent Neural Networks (RNN)

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