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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. Recently, artificial neural networks have been able to surpass many previous approaches in performance.
The following outline is provided as an overview of and topical guide to machine learning: Machine learning – subfield of soft computing within computer science that evolved from the study of pattern recognition and computational learning theory in artificial intelligence. [1] In 1959, Arthur Samuel defined machine learning as a "field of ...
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 (ML) is a type of artificial intelligence (AI) that enables computer systems to classify, cluster, identify and analyze vast and complex sets of data while eliminating the need for explicit instructions and programming. [1] Earth science is the study of the origin, evolution, and future [2] of the planet Earth.
Machine learning control. Machine learning control ( MLC) is a subfield of machine learning, intelligent control and control theory which solves optimal control problems with methods of machine learning . Key applications are complex nonlinear systems for which linear control theory methods are not applicable.
White noise may aid sleep. The most obvious benefit of white noise for babies is the fact that it could help them fall asleep. If you notice your baby tends to fall asleep at noisy times outside ...
Precision and recall. Precision and recall. In pattern recognition, information retrieval, object detection and classification (machine learning), precision and recall are performance metrics that apply to data retrieved from a collection, corpus or sample space . Precision (also called positive predictive value) is the fraction of relevant ...
v. t. e. Decision tree learning is a supervised learning approach used in statistics, data mining and machine learning. In this formalism, a classification or regression decision tree is used as a predictive model to draw conclusions about a set of observations. Tree models where the target variable can take a discrete set of values are called ...
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