Machine learning modeling Definitions
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A
AI governance
AI governance is the idea that there should be a legal framework for ensuring that machine learning (ML) technologies are well researched and developed with the goal of helping humanity navigate the adoption of AI systems fairly.
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artificial ignorance
Artificial ignorance is the artificial intelligence (AI) development practice of ignoring insignificant data in order to focus more attention to important information that might be valuable.
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C
cognitive modeling
Cognitive modeling is an area of computer science that deals with simulating human problem-solving and mental processing in a computerized model.
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concept mining
Concept mining is the process of searching documents or unstructured text for ideas and topics.
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G
generative adversarial network (GAN)
A generative adversarial network (GAN) is a type of AI machine learning (ML) technique made up of two nets that are in competition with one another in a zero-sum game framework.
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Google AutoML Vision
Google AutoML Vision is a machine learning model builder for image recognition, offered as a service from Google Cloud.
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M
machine learning bias (algorithm bias or AI bias)
Machine learning bias, also known as algorithm bias or AI bias, is a phenomenon that occurs when an algorithm produces results that are systematically prejudiced due to erroneous assumptions in the machine learning process.
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N
artificial neural network (ANN)
In information technology (IT), a neural network is a system of hardware and/or software patterned after the operation of neurons in the human brain.
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P
predictive modeling
Predictive modeling is a process that uses data mining and probability to forecast outcomes.