P

Definition: A framework in the theory of machine learning that examines the learnability of functions and the computational resources required to learn them.

Definition: In the context of data processing, especially image processing and natural language processing, padding refers to the technique of adding additional data to an input to ensure it has a fixed size or length necessary for certain models to process it.

Definition: The process of adjusting the parameters of a machine learning model to improve its performance. This is usually done by trial and error or more systematic methods such as grid search or randomised search.

Definition: The process of marking up a word in a text as corresponding to a particular part of speech, based on both its definition and its context.

Definition: The ability of a system to recognise patterns in data. It often refers to a machine learning technique that involves classifying or labelling data based on its statistical properties.

Definition: A type of artificial neural network that is especially well-suited for binary classification tasks. It’s a single-layer neural network that uses a step function as the activation function.

Definition: A technique used to construct a hash value that uniquely identifies an input data like an image or audio track based on their visual or auditory content.

Definition: A measure used to quantify the performance of a machine learning model. Common metrics include accuracy, precision, recall, F1 score, and mean squared error.

Definition: A measure used to quantify the performance of a machine learning model. Common metrics include accuracy, precision, recall, F1 score, and mean squared error.

Definition: A measure used to quantify the performance of a machine learning model. Common metrics include accuracy, precision, recall, F1 score, and mean squared error.

Definition: The smallest unit of a digital image or graphics that can be displayed and represented on a digital display device. In AI, particularly in computer vision, pixel data is used as input for models that interpret images.

Definition: A type of estimation that uses sample data to calculate a single value which is to serve as a “best guess” or “best estimate” of an unknown population parameter.

Definition: A form of regression analysis in which the relationship between the independent variable x and the dependent variable y is modelled as an nth degree polynomial.

Definition: A component of a neural network used primarily in convolutional neural networks to reduce the dimensionality of images by combining the outputs of neuron clusters.

Definition: In machine learning, precision is a metric that measures the accuracy of the positive predictions. It is the ratio of true positives to the sum of true and false positives, indicating how many of the predicted positive instances are actually positive.