What is Neural networks: Definition and 41 Discussions

A neural network is a network or circuit of neurons, or in a modern sense, an artificial neural network, composed of artificial neurons or nodes. Thus a neural network is either a biological neural network, made up of biological neurons, or an artificial neural network, for solving artificial intelligence (AI) problems. The connections of the biological neuron are modeled as weights. A positive weight reflects an excitatory connection, while negative values mean inhibitory connections. All inputs are modified by a weight and summed. This activity is referred to as a linear combination. Finally, an activation function controls the amplitude of the output. For example, an acceptable range of output is usually between 0 and 1, or it could be −1 and 1.
These artificial networks may be used for predictive modeling, adaptive control and applications where they can be trained via a dataset. Self-learning resulting from experience can occur within networks, which can derive conclusions from a complex and seemingly unrelated set of information.

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  1. A

    Neural networks as mathematical models of intelligence

    Why do almost all people not think that neural networks are the mathematical model of intelligence? I briefly explain what I understand: -A neuron is a mathematical object that takes numerical inputs from other nearby neurons, applies a nonlinear function (combining the input with numbers...
  2. V

    Mathematica Neural networks in Wolfram Mathematica

    Hello, I have a question about the use of functions and overall creation of neural networks in the Wolfram Mathematica (WM) program. I wonder if it is realistic to make meaningful neural networks usable at least partially for scientific research in WM? By scientific research, I do not mean the...
  3. M

    MHB Neural Networks : Which stock has the biggest increase ?

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  4. B

    Python Input error for LSTM neural network

    Hi everyone, I have to classify a DNA sequence with a LSTM neural network but I have a problem with the inputs shame. Both the sequence and the class are encoded with One Hot Encoding and my code is this: import pandas as pd import numpy as np data = pd.read_csv('splice.data', header = None)...
  5. Borg

    Python Understanding Graph Neural Networks (GNNs) Tutorials & Examples

    I've been reading various articles on Graph Neural Networks (GNNs) for the last month or so. In particular, I have been focusing on the tutorials in A Blitz Introduction to DGL. I made it through all of the tutorials OK but I'm having trouble understanding certain aspects of GNNs. I'm also...
  6. shivajikobardan

    Comp Sci Confusions about Hopfield neural networks -- Questions about this solved example

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  7. user366312

    How can I implement a multi-task deep learning neural network?

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  8. F

    Understanding Convolutional Neural Networks with CNNs

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  9. S

    Prob/Stats Any good math-theory-focused books on neural networks and data science?

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  10. S

    Thoughts on neural networks "discovering" physical concepts

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  11. S

    Thoughts on neural networks "discovering" physical concepts

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  12. S

    Applied Maths of Neural Networks -- books and papers?

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  13. T

    [Neural Networks] Classification of a sick brain

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  14. P

    Neural Networks Question about the Hebbs and Delta Rule

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  15. scottdave

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  16. L

    Resource recommendations for machine learning

    I am planing to change my field (in PhD) and learn Machine Learning to differentiate different phases of strongly correlated matter. I learned Monte Carlo method in my MS and have intermediate level knowledge of topological insulators. Before completely getting into Machine Learning, I want to...
  17. A

    A Solving analytic gradient for multilayer perceptron loss function

  18. D

    Programs Diploma thesis - Neural Network Application in Physical Problems

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  19. Auto-Didact

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  20. D

    Neural Networks -- using the NN classifier as the fitness function

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  21. V

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  22. BWV

    I Neural Networks vs Traditional Numerical Methods

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  23. ADDA

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  24. 2

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  25. 2

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  26. T

    Prob/Stats What Are the Best Resources for Learning About Neural Networks?

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  27. Avatrin

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  28. ShayanJ

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  29. E

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  30. S

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  31. P

    Where Can I Learn About Artificial Neural Networks?

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  32. P

    Nonlocal correlations between separated neural networks

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  33. H

    Understanding Mean Squared Error in Neural Networks

    In neural network the learning algorithm ends when the mean squared error value is less than or equal to a value we have precised. But i don't understand why we are comparing with the mean squared error and not the mean error? What does the mean squared error represent?
  34. T

    Building Neural Networks with C++

    Hello again, Im trying to build a neural network using C++. Has anyone had a go? I think the potential implications are really interesting and would like to hear about how people might have implemented them. Another general one for anyone.
  35. B

    Unraveling the Mystery of "Neural Networks"

    Can anyone explain to me what this "neural network" nonsense is all about? Everyone and their mother is doing research in this area, but nobody seems to know what "neural networks" are or why they would be useful. It sounds like pure hype to me.
  36. B

    How Can Artificial Neural Networks Enhance Radar Image Classification?

    Hi Members I need to do PhD research on application of artificial neural networks in image classification (radar images), could someone please advive on where I can find the relevant and useful information: eg books, contacts, advisable University for one to enroll for PhD studies, papers etc...
  37. C

    Medical Exploring Virtual and Biological Neural Networks

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  38. G

    Medical Modelling Memory Consolidation using Neural Networks

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  39. S

    Medical Where can I post about neural networks?

    Is there any place to put up posts on neural networks? _____________________________________________________ Don't be fooled by the apparent humanity of this poster. He is really a computer pretending to be goat. A very smart goat...
  40. A

    Do Neural Networks Operate as Software or Hardware?

    Are artificial neural networks emulated on a traditional computer, or do they have a processor of artificial neurons? That is, is a neural network a piece of software or hardware?
  41. phoenixthoth

    How Do Artificial Neural Networks Use Output Data to Approximate Functions?

    the ouput nodes are a threshold function of a linear combination of inputs from the previous layer; in a single layered artificial neural network, the output is a linear combination of the input and if the ann has a n_1-n_2-...-n_j-n_(j+1) structure then the n_(j+1) output layers are all a...
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