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What is epochs in neural network?
A step in the training process of an artificial neural network
What is momentum neural networks?
momentum neural network
Advantage and disadvantage of neural network?
Advantages and disadvantages of Artificial Neural NetworkAdvantages:· A neural network can perform tasks that a linear program cannot.· When an element of the neural network fails, it can continue without any problem by their parallel nature.· A neural network learns and does not need to be reprogrammed.· It can be implemented in any application and without any problem.Disadvantages:· The neural network needs training to operate.· The architecture of a neural network is different from the architecture of microprocessors therefore needs to be emulated.· Requires high processing time for large neural networks.
Disadvantage of artificial neural network?
the neural networks need training to operate. the architecture of a neural network is different from the architecture of microprocessor therefore needs to be emulated.
What is basic neutron of neural network?
Neural networks have nothing to do with neutrons.
What is neural network in application of Oops?
nothig
What is iteration in neural network?
gudu gudu bamboo
How does the human brain learn?
By forming an neural network
Which structure is responsible for transducing light into neural impulses?
question: what 'structure' transduces light into neural impulses? answer: a life form's 'virtual' optical neural network
Is 20Q a Neural Network?
20Q is a true neural network. The answers to questions stimulate target nodes (objects), which in turn stimulate the next question to ask. The "brain" is about as complex as an insect's brain.
What does the letters CNN mean?
A convolutional neural network (CNN) is a specific type of artificial neural network that uses perceptrons, a machine learning unit algorithm, for supervised learning, to analyze data. CNNs apply to image processing, natural language processing and other kinds of cognitive tasks. A convolutional neural network is also known as a ConvNet.
What are the advantages of sigmoidal function in neural network?
its derivative is easy to compute
