QUIZ Artificial Intelligence

Artificial Intelligence (AI)

A field of computer science focused on creating machines that can think and learn like humans by performing tasks requiring human intelligence such as perception, reasoning, and decision-making

Artificial Intelligence (AI)

A field of computer science focused on creating machines that can think and learn like humans by performing tasks requiring human intelligence such as perception, reasoning, and decision-making

Machine Learning

A subfield of AI that focuses on creating algorithms that can learn from data, with three main types: supervised, unsupervised, and reinforcement learning

Supervised Learning

A machine learning approach where the algorithm learns from labeled examples consisting of inputs and corresponding outputs to predict correct results for new inputs; also known as learning by examples

Unsupervised Learning

A machine learning approach where the algorithm finds patterns or structure in unlabeled data without prior knowledge of expected output; also known as learning by observation

Reinforcement Learning

A machine learning approach where an agent learns by interacting with an environment and receiving rewards or punishments to maximize desired outcomes; also known as learning from mistakes

Natural Language Processing (NLP)

A subfield of AI focused on the interaction between computers and human language, used in virtual assistants, chatbots, language translation, and sentiment analysis

Tokenization

An NLP task that involves breaking a text into individual words or phrases called tokens

Part-of-Speech Tagging

An NLP task that identifies the part of speech such as noun, verb, or adjective of each word in a sentence

Named Entity Recognition

An NLP task that identifies and classifies named entities such as people, organizations, and locations in a text

Sentiment Analysis

An NLP task that determines the sentiment expressed in a text, whether positive, negative, or neutral

Computer Vision

A subfield of AI that enables machines to interpret and understand visual data from digital images and videos to extract information and make decisions

Object Recognition

A computer vision technique used to identify and localize objects within an image or video

Image Classification

A computer vision technique that assigns a label or category to an image based on its content

Deep Learning

A subset of machine learning that uses neural networks with many layers to learn from large datasets, applied in computer vision, NLP, and robotics

Robotics

The combination of AI, machine learning, and engineering to create intelligent machines that can interact with the physical world, with applications in manufacturing, healthcare, and transportation

AI Bias

A situation where AI systems produce biased decisions due to biased or incomplete training data, such as facial recognition algorithms being less accurate in recognizing people of color

AI Ethics

The study and application of moral principles in AI development covering areas such as fairness and bias, trust and transparency, accountability, social benefit, and privacy and security

Model-Based Reinforcement Learning

A type of reinforcement learning that builds a model of the environment and uses it to make predictions about the outcomes of actions

Model-Free Reinforcement Learning

A type of reinforcement learning that does not rely on a model and instead learns directly from experience