machine learning


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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.
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That being said, it's worth figuring out how and where carefully applied machine learning could add significant value.
Computing power improved to allow analysis of the tremendous amount of data being produced, and faster computing led to an increase in academic research on machine learning and artificial intelligence.
One of the most challenging aspects of finding opportunities for machine learning and carrying out an Al-driven project is the need to shift preconceived notions of how traditional tasks are currently accomplished.
This involves collecting large amounts of data (big data) around how humans make decisions then feed it to advanced machine learning algorithms that can learn and automate the mundane decisions.
With mounting pressure from increased competition, a highly elastic marketplace, complex claims and fraud behavior, and a tighter regulatory environment, insurance carriers can no longer maintain a competitive edge without predictive modeling and machine learning.
John May, chief information officer and president of agricultural solutions at John Deere, called machine learning "an important capability for Deere's future".
Adaptive Learning, Machine Learning, and Cognitive Search
MACHINE LEARNING ALLOWS ENDPOINT SECURITY TO CONTINUALLY EVOLVE TO STOP NEW ATTACK TACTICS
Machine learning is helping our lives become more enabled, streamlined, and friction-free.
You can read a lot more about machine learning in this article.
He thinks companies are well motivated to find ways to make automated machine learning practical.
Machine learning is proving its value in the clinical quality improvement sphere.

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