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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]
Key topics include machine learning, deep learning, natural language processing and computer vision. Many universities now offer specialized programs in AI engineering at both the undergraduate and postgraduate levels, including hands-on labs, project-based learning, and interdisciplinary courses that bridge AI theory with engineering practices ...
How deep learning is a subset of machine learning and how machine learning is a subset of artificial intelligence (AI) The deep learning revolution started around CNN- and GPU-based computer vision. Although CNNs trained by backpropagation had been around for decades and GPU implementations of NNs for years, [112] including CNNs, [113] faster ...
The plain transformer architecture had difficulty converging. In the original paper [1] the authors recommended using learning rate warmup. That is, the learning rate should linearly scale up from 0 to maximal value for the first part of the training (usually recommended to be 2% of the total number of training steps), before decaying again.
In computer science, computational learning theory (or just learning theory) is a subfield of artificial intelligence devoted to studying the design and analysis of machine learning algorithms. [ 1 ] Overview
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]
Machine learning (ML) is a subfield of artificial intelligence within computer science that evolved from the study of pattern recognition and computational learning theory. [1] In 1959, Arthur Samuel defined machine learning as a "field of study that gives computers the ability to learn without being explicitly programmed". [ 2 ]
According to Bezdek (1994), while Computational Intelligence is a subset of Artificial Intelligence indeed, there are two types of machine intelligence: the artificial one based on hard computing techniques and the computational one based on soft computing methods, which enable adaptation to many situations.