Sampling
Selecting a subset of data from a larger dataset to make statistical inferences or train models.
Common AI terms beginning with S, 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 “S”.
Selecting a subset of data from a larger dataset to make statistical inferences or train models.
Adjusting numerical data into a specified range to improve learning stability.
In optimization, a plan for adjusting the learning rate over the course of training.
A mechanism that allows models to weigh the importance of different parts of an input sequence relative to each other.
Learning from data without explicit labels by creating proxy tasks, such as predicting the next word in a sentence.
Assigning a class label to each pixel in an image to delineate objects and backgrounds.
Using NLP techniques to determine the emotional tone of text, such as positive, negative or neutral.
Models designed to handle sequential data, such as time series or language, by capturing order and context.
Data where order matters, such as clickstreams, sensor readings or sentences.
An activation function that maps input values into a range between 0 and 1.
A measure that quantifies how alike two data points are, used in clustering and recommendation.
A matrix factorisation technique used for dimensionality reduction and latent semantic analysis.
A direct connection that bypasses one or more layers in a neural network, helping to combat vanishing gradients.
An activation function that converts a vector of values into probabilities that sum to 1.
The proportion of true negatives correctly identified by a model, important for evaluating classifiers.
Converting spoken language into text using AI models and signal processing.
Transforming data to have zero mean and unit variance.
In reinforcement learning, the current situation that the agent observes and uses to decide actions.
Methods that use statistics to infer relationships from data and make predictions.
An iterative optimisation algorithm that updates model parameters using random subsets (batches) of data.
Recombining the style of one image with the content of another using neural networks, useful for creative campaigns.
Training models on labelled data where the correct output is provided for each input.
A supervised learning algorithm that finds the optimal hyperplane separating classes in the feature space.
Data artificially generated to augment training sets or protect privacy while preserving statistical properties.
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