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Introduction To Neural Networks Using MATLAB 60 By S N Sivanandam Sumathi Amp Deepahottorrent

in this course, you will learn:

  • neurons: how neurons perform computations using information passed from other neurons and how these neurons compute the output of a given input
  • hidden layers: the idea behind neural networks, in particular, artificial neural networks. this is the most important component in neural networks, helps them to perform complex tasks like classification, regression etc.
  • inputs: there are many types of inputs, like images, videos, text, audio, time series, graphs etc. if your problem is about a set of images, they are known as inputs. the data is fed to the network and the results are passed back to us
  • outputs: the actual answer you want to get. for example, if you want to classify an image, the output is the class you want to assign to the image.
  • training: how to build and train a neural network
  • testing: how to test and evaluate your neural network

you will get:

  • the step-by-step process to build your own neural network
  • matlab commands to build and test your neural network
  • matlab commands to train, test, predict and analyse your neural network
  • matlab commands to handle different inputs
  • matlab commands to handle different outputs
  • a ready to use neural network
  • an insight into the problem of working with neural networks
  • a clear understanding of what neural networks can do for you
  • an idea of what neural networks can not do

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