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The computational analysis of machine learning algorithms and their performance is a branch of theoretical computer science known as computational learning theory via the Probably Approximately Correct Learning (PAC) model. Because training sets are finite and the future is uncertain, learning theory usually does not yield guarantees of the ...
Albert Bandura. Albert Bandura (December 4, 1925 – July 26, 2021) was a Canadian-American psychologist. He was a professor of social science in psychology at Stanford University. [1] Bandura was responsible for contributions to the field of education and to several fields of psychology, including social cognitive theory, therapy, and ...
Indiana University. Harvard University. Signature. Burrhus Frederic Skinner (March 20, 1904 – August 18, 1990) was an American psychologist, behaviorist, inventor, and social philosopher. [2][3][4][5] He was the Edgar Pierce Professor of Psychology at Harvard University from 1958 until his retirement in 1974. [6]
Learning sciences (LS) is the critical theoretical understanding of learning, [1] engagement in the design and implementation of learning innovations, and the improvement of instructional methodologies. LS research traditionally focuses on cognitive-psychological, social-psychological, cultural-psychological and critical theoretical foundations ...
Jean William Fritz Piaget (UK: / piˈæʒeɪ /, [1][2] US: / ˌpiːəˈʒeɪ, pjɑːˈʒeɪ /; [3][4][5] French: [ʒɑ̃ pjaʒɛ]; 9 August 1896 – 16 September 1980) was a Swiss psychologist known for his work on child development. Piaget's theory of cognitive development and epistemological view are together called genetic epistemology.
t. e. In machine learning, a neural network (also artificial neural network or neural net, abbreviated ANN or NN) is a model inspired by the structure and function of biological neural networks in animal brains. [1][2] An ANN consists of connected units or nodes called artificial neurons, which loosely model the neurons in the brain.
Deep learning is a subset of machine learning that focuses on utilizing neural networks to perform tasks such as classification, regression, and representation learning. The field takes inspiration from biological neuroscience and is centered around stacking artificial neurons into layers and "training" them to process data.
e. Reinforcement learning (RL) is an interdisciplinary area of machine learning and optimal control concerned with how an intelligent agent should take actions in a dynamic environment in order to maximize a reward signal. Reinforcement learning is one of the three basic machine learning paradigms, alongside supervised learning and unsupervised ...