AUC (Area Under the Curve)

A model's probability of choosing a positive instance over a negative instance.

Azure Machine Learning

A cloud-based tool used to build AI models.

A test in which different app versions are shown to different people and usage patterns and responses are compared to each other.

An imbalance in data that can cause data to be skewed toward a demographic group, which can harm an AI machine-learning model.

A form of data that stores data as ones and zeros.

A model type in which a result is categorized, usually with one of two values, such as a yes or no value.

The process of identifying and correcting or removing errors, inconsistencies, and inaccuracies in data.

The change in the underlying concepts used to train AI models.

A chart that defines true and false positives and true and false negatives for an AI model.

A limitation or restriction on an AI system.

A measure of connection between two points of data.

The financial investment required to develop, deploy, and maintain an AI model.

Data stored on an on-premises or cloud storage drive.

The change in the statistical properties of the input data within an AI model.

Data in the process of being copied or moved from one location to another.

A characteristic of data, such as numeric, string, or date.

Decision Tree Algorithm

A machine learning method in which samples are split into two or more sets of data based on input variable differentiators.

Deep Learning Algorithm

An algorithm used for neural networks, which work with AI models for human-based interaction.

The act of no longer using an AI model in production due to its lack of effectiveness.

Degraded Mode of Operation

A mode of operation in which an AI model is not performing to its maximum capabilities.

A feature built using a formula, through splitting or combining data, or through assigning keywords to data based on conditions.

A mechanism that identifies shifts in the underlying data used in an AI solution.

A test in which an AI system's performance is pushed beyond its normal operating range.

Explainability Requirement

A clear explanation for a decision, prediction, or recommendation made from an AI model.

The harmonic mean of precision and recall.

An incorrect negative result for an AI model.

An incorrect positive result for an AI model.

An input to an AI model used to generate output.

The process of transforming and manipulating data to make it more suitable for an AI model.

An ordered list of numerical properties of observed phenomena.

A means by which feedback is collected for an AI system, whether that be through forms, a website, or directly within the system.

GDPR (General Data Protection Regulation)

The European Union (EU) standard for handling data that affects companies doing business in the EU.

A repository used to store code for development projects.

A dataset that has too much data from one or more groups of data.

The ability for one to understand the results of an AI model.

A sequence of training an AI model, often needs to be repeated to fully train an AI model.

JSON (JavaScript Object Notation)

A file format in which data is stored in key-value pairs.

A machine learning model that splits data into an unspecified number of groups.

KPI (Key Performance Indicator)

A visualization that sets standards for performance for, in the context of AI, AI models.

Data that is paired with output targets in an AI model.

A form of regression in which an outcome is a continuous variable, like a number.

A list of activities in an AI model that can be used to identify potential security problems with a model.

A form of regression in which an outcome uses binary dependent variables.

An app used to generate predictions and outcomes based on the entering and training of data entered into the app.

AI and Machine Learning Terminology Flashcards

Student preview

94 questions

Show all answers

1.

FLASHCARD QUESTION

Front

Accuracy

Back

The percentage of correct predictions within a model.

2.

FLASHCARD QUESTION

Front

AI (Artificial Intelligence)

Back

Intelligence that can be programmed to mimic human intelligence.

3.

FLASHCARD QUESTION

Front

Algorithm

Back

A set of rules used to generate calculations or perform problem-solving operations.

4.

FLASHCARD QUESTION

Front

Anomaly

Back

An unusual activity in a group of otherwise normal activities.

5.

FLASHCARD QUESTION

Front

API (Application Programming Interface)

Back

A set of rules that allows applications to communicate with each other.

6.

FLASHCARD QUESTION

Front

Assumption

Back

A belief or condition taken to be true for a system to work as intended.

7.

FLASHCARD QUESTION

Front

Attack Surface

Back

The parts of data or a system that are vulnerable to attack.

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