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Transfer of learning. Transfer of learning occurs when people apply information, strategies, and skills they have learned to a new situation or context. Transfer is not a discrete activity, but is rather an integral part of the learning process. Researchers attempt to identify when and how transfer occurs and to offer strategies to improve ...
Transfer learning (TL) is a technique in machine learning (ML) in which knowledge learned from a task is re-used in order to boost performance on a related task. For example, for image classification , knowledge gained while learning to recognize cars could be applied when trying to recognize trucks.
Learning theory (education) A classroom in Norway. Learning theory describes how students receive, process, and retain knowledge during learning. Cognitive, emotional, and environmental influences, as well as prior experience, all play a part in how understanding, or a worldview, is acquired or changed and knowledge and skills retained. [1] [2]
Theoretically, transfer of training is a specific application of the theory of transfer of learning that describes the positive, zero, or negative performance outcomes of a training program. [2] The positive transfer of training-- the increase in job performance attributed to training-- has become the goal of many organizations.
e. Learning is the process of acquiring new understanding, knowledge, behaviors, skills, values, attitudes, and preferences. [1] The ability to learn is possessed by humans, non-human animals, and some machines; there is also evidence for some kind of learning in certain plants. [2] Some learning is immediate, induced by a single event (e.g ...
In deep learning, fine-tuning is an approach to transfer learning in which the parameters of a pre-trained model are trained on new data. [1] Fine-tuning can be done on the entire neural network, or on only a subset of its layers, in which case the layers that are not being fine-tuned are "frozen" (not updated during the backpropagation step). [2]
Language transfer is the application of linguistic features from one language to another by a bilingual or multilingual speaker. Language transfer may occur across both languages in the acquisition of a simultaneous bilingual, from a mature speaker's first language (L1) to a second language (L2) they are acquiring, or from an L2 back to the L1. [1]
Self-supervised learning (SSL) is a paradigm in machine learning where a model is trained on a task using the data itself to generate supervisory signals, rather than relying on external labels provided by humans. In the context of neural networks, self-supervised learning aims to leverage inherent structures or relationships within the input ...