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AI > AI Terms [Coursera] > Flashcards

AI Terms [Coursera] Flashcards

1
Q

AI (artificial intelligence)

A

AI stands for artificial intelligence, which is the simulation of human intelligence processes by machines or computer systems. AI can mimic human capabilities such as communication, learning, and decision-making.

Coursera: AI Terms

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2
Q

AI ethics

A

AI ethics refers to the issues that AI stakeholders must consider to ensure technology is developed and used responsibly, including a safe, secure, unbiased, and environmentally friendly approach.

Coursera: AI Terms

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3
Q

Algorithm

A

A sequence of rules given to an AI machine to perform a task or solve a problem, including classification, regression, and clustering.

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4
Q

Application programming interface (API)

A

A set of protocols that determine how two software applications interact, often written in languages like C++ or JavaScript.

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5
Q

Big data

A

Refers to large datasets that reveal patterns and trends for business decisions, often gathered and stored quickly in diverse formats.

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6
Q

Chatbot

A

A software application designed to imitate human conversation through text or voice commands.

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7
Q

Cognitive computing

A

Similar to AI, it focuses on mimicking human thought processes like pattern recognition and learning, sometimes used to reduce the sci-fi perception of AI.

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8
Q

Computer vision

A

An interdisciplinary field focusing on how computers can interpret images and videos, allowing for automation of tasks the human visual system typically performs.

Coursera: AI Terms

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9
Q

Data mining

A

The process of analyzing large datasets to identify patterns that can improve models or solve problems.

Coursera: AI Terms

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10
Q

Data science

A

An interdisciplinary field using algorithms and processes to gather and analyze large amounts of data, uncovering patterns for business insights.

Coursera: AI Terms

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11
Q

Deep learning

A

A function of AI that imitates human brain structures to make decisions, learning from unstructured data without supervision.

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12
Q

Emergent behavior

A

When an AI system displays unpredictable or unintended capabilities.

Coursera: AI Terms

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13
Q

Generative AI

A

Technology that uses AI to create content such as text, video, code, and images, often using models trained on large datasets.

Coursera: AI Terms

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14
Q

Guardrails

A

Restrictions placed on AI systems to ensure appropriate data handling and prevent unethical content generation.

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15
Q

Hallucination

A

An incorrect response or false information generated by an AI system, presented as factual.

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16
Q

Hyperparameter

A

A parameter that affects how an AI model learns, typically set manually outside the model.

Coursera: AI Terms

17
Q

Image recognition

A

The process of identifying objects, people, places, or text within an image or video.

Coursera: AI Terms

18
Q

Large language model

A

An AI model trained on vast text datasets to understand and generate human-like language, including technologies like GPT and BERT.

Coursera: AI Terms

19
Q

Limited memory

A

AI systems that use real-time data to make better predictions by storing past events.

Coursera: AI Terms

20
Q

Machine learning

A

A subset of AI focusing on algorithms and models that help machines learn from data and predict trends without human assistance.

Coursera: AI Terms

21
Q

Natural language processing (NLP)

A

A type of AI enabling computers to understand and process human language, including speech and text recognition.

Coursera: AI Terms

22
Q

Neural network

A

A deep learning technique resembling the human brain, requiring large datasets to perform calculations for tasks like speech and vision recognition.

Coursera: AI Terms

23
Q

Overfitting

A

When a machine learning model is too tailored to its training data, limiting its ability to generalize to new data.

Coursera: AI Terms

24
Q

Pattern recognition

A

The method of using algorithms to detect and classify regularities in data.

Coursera: AI Terms

25
Q

Predictive analytics

A

Analytics that use historical data and patterns to forecast future events within a specific timeframe.

Coursera: AI Terms

26
Q

Prescriptive analytics

A

Analytics used to make strategic decisions by analyzing data on potential scenarios, past performance, and available resources.

Coursera: AI Terms

27
Q

Prompt

A

An input given to an AI system to produce a specific output.

Coursera: AI Terms

28
Q

Quantum computing

A

A computing method using quantum-mechanical phenomena, allowing faster calculations for tasks like machine learning.

Coursera: AI Terms

29
Q

Reinforcement learning

A

A machine learning method where an algorithm learns by interacting with its environment, receiving rewards or penalties based on actions.

Coursera: AI Terms

30
Q

Sentiment analysis

A

Also known as opinion mining, it analyzes the tone or opinion within text data.

Coursera: AI Terms

31
Q

Structured data

A

Defined and searchable data, including elements like phone numbers, dates, and product SKUs.

Coursera: AI Terms

32
Q

Supervised learning

A

A machine learning method where classified output data trains the model to produce correct algorithms.

Coursera: AI Terms

33
Q

Token

A

A basic unit of text in language models, which can be a word or part of a word.

Coursera: AI Terms

34
Q

Training data

A

Data used to teach an AI system to identify patterns and create new content.

Coursera: AI Terms

35
Q

Transfer learning

A

A machine learning method where previously learned data is applied to new tasks for enhanced performance.

Coursera: AI Terms

36
Q

Turing test

A

A test developed by Alan Turing to assess whether a machine’s responses are indistinguishable from a human’s.

Coursera: AI Terms

37
Q

Unstructured data

A

Data that lacks a defined format, such as audio, video, and images, which are difficult to search.

Coursera: AI Terms

38
Q

Unsupervised learning

A

A machine learning method where an algorithm learns patterns from unclassified data, without supervision.

Coursera: AI Terms

39
Q

Voice recognition

A

Also known as speech recognition, it enables computers to interpret spoken language and produce responses or written outputs.

Coursera: AI Terms

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