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Further, you will learn to implement some more complex types of neural networks such as convolutional neural networks, recurrent neural networks, and Deep Belief Networks. In the course of the book, you will be working on real-world datasets to get a hands-on understanding of neural network programming. You will also get to train generative models and will learn the applications of …...
Intelligent Systems: Approximation by Artificial Neural Networks Book Description: This brief monograph is the first one to deal exclusively with the quantitative approximation by artificial neural networks to the identity-unit operator.

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The main goal of the book is to explain the principles of neural networks and fuzzy systems and to demonstrate how they can be applied to building knowledge-based systems for problem solving.

  • 2/08/2012 · It is then compiled into an efficient neural network (NN) representation, run, and the results from run time and (eventually) from learning are decompiled to a symbolic description of the knowledge contained in the network . After inspecting this recovered knowledge, a designer would be able to modify the KB and go through the whole cycle of compiling, running, and decompiling again, as
  • Intelligent Systems: Approximation by Artificial Neural Networks Book Description: This brief monograph is the first one to deal exclusively with the quantitative approximation by artificial neural networks to the identity-unit operator.
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