Machine Learning
A subset of AI that trains models on data to make predictions or decisions without being explicitly programmed.
Common AI terms beginning with M, defined for advertising professionals.
Find the Flux+Form AI glossary & dictionary to help you make sense of common AI terms. Below you can find an AI Glossary & Dictionary for “M”.
A subset of AI that trains models on data to make predictions or decisions without being explicitly programmed.
Techniques that uncover low‑dimensional structures hidden in high‑dimensional data.
In classification, the distance between data points and the decision boundary; larger margins typically indicate better generalisation.
Software and AI‑driven workflows that streamline and automate marketing activities across channels.
Statistical analysis that quantifies the impact of different marketing channels on sales, enabling more efficient budget allocation.
Coordinating personalized marketing interactions across multiple channels using AI to determine the best next action.
A mathematical framework for modelling decision making where outcomes are partly random and partly under the control of a decision maker.
A method for estimating model parameters by maximizing the probability of observing the given data.
The process of determining when, where and how often ads should run; AI models help optimise placements based on audience data.
Techniques where models learn how to learn, enabling rapid adaptation to new tasks with minimal training examples.
Learning a distance function that reflects task‑specific notions of similarity, improving recommendation and clustering.
A probabilistic model that assumes data are generated from a mixture of underlying distributions, often used in segmentation.
Techniques for reducing the size of models to deploy them efficiently on edge devices.
An open standard that defines how AI models connect to external tools, data sources, and services — a universal adapter that enables agentic AI workflows without custom integration for every combination.
Training a smaller, faster AI model to replicate the performance of a larger one, producing a model that is cheaper to run while retaining most of the capability that matters for a specific task.
Gradual degradation in model performance due to changing data distributions or customer behaviour.
A setup where multiple AI agents work together — each handling a distinct part of a task — enabling agencies to automate complex multi-step workflows from research to delivery.
Algorithms that balance exploration and exploitation to maximise reward, used in real‑time ad selection.
Training models that can process and integrate multiple types of data (e.g., text, images and audio).
Assigning credit to the multiple marketing interactions that influence a customer’s decision, often using AI models.
High correlation among independent variables in regression analysis, which can make estimates unstable.
Predicting an outcome variable using multiple predictors; common in marketing performance modelling.
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