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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. [1]
1950s. Pioneering machine learning research is conducted using simple algorithms. 1960s. Bayesian methods are introduced for probabilistic inference in machine learning. [1] 1970s. ' AI winter ' caused by pessimism about machine learning effectiveness. 1980s.
This book is considered by some to mark the beginning of the AI winter of the 1970s, a failure of confidence and funding for AI. However, by the time the book came out, methods for training multilayer perceptrons by deep learning were already known (Alexey Grigorevich Ivakhnenko and Valentin Lapa, 1965; Shun'ichi Amari, 1967).
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 ...
Tom Michael Mitchell (born August 9, 1951) is an American computer scientist and the Founders University Professor at Carnegie Mellon University (CMU). He is a founder and former Chair of the Machine Learning Department at CMU. [4] Mitchell is known for his contributions to the advancement of machine learning, artificial intelligence, and ...
Researchers in the United Kingdom had been exploring "machine intelligence" for up to ten years prior to the founding of the field of artificial intelligence ( AI) research in 1956. [5] It was a common topic among the members of the Ratio Club, an informal group of British cybernetics and electronics researchers that included Alan Turing.
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