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Supervised learning; Unsupervised learning; Semi-supervised learning; Self-supervised learning; Reinforcement learning; Meta-learning; Online learning; Batch learning; Curriculum learning; Rule-based learning; Neuro-symbolic AI; Neuromorphic engineering; Quantum machine learning
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]
The adherents of machine aesthetic called for elimination of traditional for architecture (and furniture design) structural distinctions between load and support. For example, in the Red and Blue Chair (1917) the (red) back plays the role of the load (supported by a crossbar underneath the seat) and provides support for the arms at the same ...
Feature learning is intended to result in faster training or better performance in task-specific settings than if the data was input directly (compare transfer learning). [1] In machine learning (ML), feature learning or representation learning [2] is a set of techniques that allow a system to automatically discover the representations needed ...
Artificial intelligence (AI), in its broadest sense, is intelligence exhibited by machines, particularly computer systems.It is a field of research in computer science that develops and studies methods and software that enable machines to perceive their environment and use learning and intelligence to take actions that maximize their chances of achieving defined goals. [1]
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 ...