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e. Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data and thus perform tasks without explicit instructions. [1] Recently, artificial neural networks have been able to surpass many previous approaches in ...
e. Active learning is a special case of machine learning in which a learning algorithm can interactively query a human user (or some other information source), to label new data points with the desired outputs. The human user must possess knowledge/expertise in the problem domain, including the ability to consult/research authoritative sources ...
Machine learning involves the study and construction of algorithms that can learn from and make predictions on data. [3] These algorithms operate by building a model from an example training set of input observations to make data-driven predictions or decisions expressed as outputs, rather than following strictly static program instructions.
Google JAX is a machine learning framework for transforming numerical functions. [69] [70] [71] It is described as bringing together a modified version of autograd (automatic obtaining of the gradient function through differentiation of a function) and TensorFlow's XLA (Accelerated Linear Algebra).
Statistical learning theory is a framework for machine learning drawing from the fields of statistics and functional analysis. [1][2][3] Statistical learning theory deals with the statistical inference problem of finding a predictive function based on data. Statistical learning theory has led to successful applications in fields such as ...
Glossary. v. t. e. Artificial general intelligence (AGI) is a theoretical type of artificial intelligence (AI) that falls within the lower and upper limits of human cognitive capabilities across a wide range of cognitive tasks. [1][2][3] This contrasts with narrow AI, which is limited to specific tasks. [4] Artificial superintelligence (ASI ...
Educational data mining. Educational data mining (EDM) is a research field concerned with the application of data mining, machine learning and statistics to information generated from educational settings (e.g., universities and intelligent tutoring systems). At a high level, the field seeks to develop and improve methods for exploring this ...
Fundamentally, deep learning refers to a class of machine learning algorithms in which a hierarchy of layers is used to transform input data into a slightly more abstract and composite representation. For example, in an image recognition model, the raw input may be an image (represented as a tensor of pixels). The first representational layer ...