Примери за използване на Artificial neural networks на Английски и техните преводи на Български
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Artificial neural networks.
Deep learning and artificial neural networks.
Artificial neural networks/ANN/ have many applications.
It is also called as'Artificial Neural Networks'.
Artificial neural networks follow this principle.
Process modelling using artificial neural networks.
The artificial neural networks functions in the same manner.
Modeling and analysis of time series with artificial neural networks.
Use of artificial neural networks in disease prediction.
Hebbs suggested a way in which artificial neural networks might learn.
Artificial neural networks decode brain activity during performed and imagined movements.
This is true of artificial neural networks as well.
This new device is flexible and versatile,which is highly desirable in artificial neural networks.
We now can train artificial neural networks in the time it would take to make a cup of coffee.
This paper is an attempt to introduce the essence and methodology of Artificial Neural Networks(ANN) in marketing.
Artificial neural networks could be our next step in creating a real artificial intelligence.
The artificial neural networks that made face and voice recognition viable were the low-hanging fruit.
Perceptrons: Written with Seymour Papert became the foundational work in the analysis of artificial neural networks.
Analysis of the architecture of artificial neural networks and training classifiers on a limited set of data MNIST.
Minsky wrote the book Perceptrons(with Seymour Papert),which became the foundational work in the analysis of artificial neural networks.
Is discussing the application of direct and recurrent artificial neural networks(ANN) in some methodologies for credit risk models.
BNNS is an open source(GPL)software that uses the Response Function Plots visualization method to train artificial neural networks.
Artificial neural networks already run our internet search engines, digital assistants, self-driving cars, Wall Street trading algorithms, and smart phones.
Minsky wrote the book Perceptrons(with Seymour Papert), attacking the work of Frank Rosenblatt,which became the foundational work in the analysis of artificial neural networks.
Conventional software operates within strict parameters but artificial neural networks have the ability to“learn” by being fed more and more data over time.
Deep Learning is a subfield of machine learning concerned with algorithms inspired by structure andfunction of brain called artificial neural networks.
Discoveries in neuroscience could be applied to the construction of advanced artificial neural networks, with the possibility of learning, growing, and adapting.
Such a network of algorithms are called artificial neural networks, being named so as their functioning is an inspiration, or you may say; an attempt at imitating the function of the human neural networks present in the brain.
In the field of computer science, the study of bionics has produced artificial neurons, artificial neural networks, and swarm intelligence.