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etimologia

Cosa (chi) è neural network - definizione

COMPUTATIONAL MODEL USED IN MACHINE LEARNING, BASED ON CONNECTED, HIERARCHICAL FUNCTIONS

Neural net; Neural nets; Massive neural network; Neuralnets; Neuralnet; Artificial neural networs; Artificial neural networks; Artificial Neural Networks; Distributed representation; Nervous network; Nueral Network; Simulated neural network; Artificial Neural Network; Simulated Neural Network; Neural Network; Stochastic neural network; Present challenges in neural Networks; Problems in the verge of success in neural network research; Nervous Network; Bayesian neural network; Nueral networks; Neural network processor; Neural network processors; Neural computing; Neural circuitry; Neural Nets; Neural networks in robotics; Artificial neural net; Fuzzy neural networks; Neural network (computer); Neural network models; Neural network model; Models of neural network; Models of neural networks; Neural networks (computer); Aritificial Neuron Network; Computational network; History of Neural Networks; Convergent recursive learning algorithm; Deep stacking network; Tensor deep stacking network; Deep predictive coding networks; Applications of artificial neural networks; Neural network (artificial); Algorithms for training neural networks; Parameter (machine learning); Criticism of artificial neural networks; Self-learning in artificial neural network

neural network

STRUCTURE IN BIOLOGY AND ARTIFICIAL INTELLIGENCE

Neural networks; History of neural networks; Applications of neural networks

artificial neural network

neural network

STRUCTURE IN BIOLOGY AND ARTIFICIAL INTELLIGENCE

Neural networks; History of neural networks; Applications of neural networks

(neural networks)

In computing, a neural network is a program or system which is modelled on the human brain and is designed to imitate the brain's method of functioning, particularly the process of learning.

N-COUNT

neural network

STRUCTURE IN BIOLOGY AND ARTIFICIAL INTELLIGENCE

Neural networks; History of neural networks; Applications of neural networks

(also neural net)

¦ noun a computer system modelled on the human brain and nervous system.

Wikipedia

Artificial neural network

Artificial neural networks (ANNs), usually simply called neural networks (NNs) or neural nets, are computing systems inspired by the biological neural networks that constitute animal brains.

An ANN is based on a collection of connected units or nodes called artificial neurons, which loosely model the neurons in a biological brain. Each connection, like the synapses in a biological brain, can transmit a signal to other neurons. An artificial neuron receives signals then processes them and can signal neurons connected to it. The "signal" at a connection is a real number, and the output of each neuron is computed by some non-linear function of the sum of its inputs. The connections are called edges. Neurons and edges typically have a weight that adjusts as learning proceeds. The weight increases or decreases the strength of the signal at a connection. Neurons may have a threshold such that a signal is sent only if the aggregate signal crosses that threshold.

Typically, neurons are aggregated into layers. Different layers may perform different transformations on their inputs. Signals travel from the first layer (the input layer), to the last layer (the output layer), possibly after traversing the layers multiple times.

https://en.wikipedia.org/wiki/Artificial neural network

Esempi dal corpus di testo per neural network

1. The bulk of Wikipedia‘s errors came from a few entries: "Dmitry Mendeleev", "Acheulean industry" "neural network" and "prion" were the worst offenders.

2. "The point of a brain is that it‘s not one huge neural network with feedback, it has up to 50 to 60 identified areas, all of which have feedback and all of which are capable of knowledge storage.

3. An artificial neural network could be made to switch on when it "sees" something it knows – a tortoise, say – and it will learn to associate a certain pattern of neuron activity with it.

4. "We also found out digitally that Van Gogh used those combinations like blue next to yellowy–orange to highlight certain things in his paintings – a female figure wearing a blue dress, for example, and the background of bright orange." The next step is to attach a neural network to the software so that it can learn further details about a painter.