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About Neural Networks
Neural networks is a book that provides a solid basis for simple neural network concepts. It incorporates a top level view of neural network architectures for practical information analysis done with the aid of extensive step-by-step analysis on linear networks, in addition to, multi-layer perceptron for nonlinear prediction and classification enlightening all stages of processing and model development explained through useful examples and case studies. It gives an in depth coverage on Self organization for nonlinear information clustering, recurrent networks for linear nonlinear time series forecasting, and different community kinds appropriate for scientific record analysis. What to expect from this book: Overview of Neural Networks How Neural Networks differ from conventional computing Forex trading using Neural Networks for huge profits Applications which are appropriate for Neural Network Mind-Mapping Neural Network Schematic models How artificial Neural Networks can help in medicine Integration of new Neurons into neural networks And much, much more! Neural Network is a key element of deep learning processes and artificial intelligence, which these days is capable of some genuinely outstanding feats. But only few people truly know how neural network actually functions. This manual will take you on a fun and simple route, beginning from very simple thoughts, and progressively building up an understanding of ways Neural Networks works. You might not really need any further knowledge other than your secondary school. So the aim of this book is to make neural network as available and accessible to as many readers as possible. It is ideal for both beginners and advanced readers alike! You will learn to code using Python programming language and will also be able to make your own neural network, teaching it to recognize human handwritten numbers, and performing as well as professionally developed networks. Raghava Shankar’s witty, engaging writing skills makes this
