machine learning

[mə′shēn ‚lərn·iŋ] (computer science) The process or technique by which a device modifies its own behavior as the result of its past experience and performance.

machine learning

The ability of a machine to improve its performance based onprevious results.

Neural networks are one kind of machine learning.

machine learning

Artificial intelligence (AI) software that modifies its own algorithms in order to become more intelligent and improve future results. Machine learning is used in numerous disciplines, including medical diagnosis, ad serving, spam filtering, sales forecasting and computer vision.

Unlike the static logic (if this - do that) in regular programs, machine learning continues to refine its logic over time and with enough samples so that the next operation is more effective than the last. Today's virtual assistants are often a combination of machine learning, which relies on neural networks, and "handcrafting," which provides predefined frameworks for responses. See neural network and deep learning.

machine learning

The integration of patterns and cues by a computer so that it can perform certain tasks—e.g., approving a person for credit and reading zip codes from handwriting. Machine learning (ML) is based on a computer’s behaviour, which can be viewed as a function that associates input values (the specifics of a problem to be solved) with the corresponding output values (the decision or action to be made). The most common form of ML is the neural network, which allows for learning through the back-propagation algorithm, using simple calculus to decide how to change the parameters of the neural network.

单词	machine learning
释义	machine learning machine learning n (Computer Science) a branch of artificial intelligence in which a computer generates rules underlying or based on raw data that has been fed into it machine learning machine learning [mə′shēn ‚lərn·iŋ] (computer science) The process or technique by which a device modifies its own behavior as the result of its past experience and performance. machine learning The ability of a machine to improve its performance based onprevious results. Neural networks are one kind of machine learning. machine learning Artificial intelligence (AI) software that modifies its own algorithms in order to become more intelligent and improve future results. Machine learning is used in numerous disciplines, including medical diagnosis, ad serving, spam filtering, sales forecasting and computer vision. Unlike the static logic (if this - do that) in regular programs, machine learning continues to refine its logic over time and with enough samples so that the next operation is more effective than the last. Today's virtual assistants are often a combination of machine learning, which relies on neural networks, and "handcrafting," which provides predefined frameworks for responses. See neural network and deep learning. machine learning machine learning The integration of patterns and cues by a computer so that it can perform certain tasks—e.g., approving a person for credit and reading zip codes from handwriting. Machine learning (ML) is based on a computer’s behaviour, which can be viewed as a function that associates input values (the specifics of a problem to be solved) with the corresponding output values (the decision or action to be made). The most common form of ML is the neural network, which allows for learning through the back-propagation algorithm, using simple calculus to decide how to change the parameters of the neural network. LegalSeeAIAcronymsSeemLThesaurusSeeneural network
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