Multilayer Perceptron: Fundamentals and Applications for Decoding Neural Networks
About this eBook
A fully connected class of feedforward artificial neural network (ANN), a multilayer perceptron, or MLP, is referred to as a multilayer perceptron. The word "MLP" is used in a way that is rather vague. Sometimes it is used to refer to any feedforward ANN, and other times it is used more specifically to refer to networks that are constructed of several layers of perceptrons; for more information, see "Terminology." When they just contain one hidden layer, multilayer perceptrons are sometimes jokingly referred to as "vanilla" neural networks. This is especially true when the term is used in a slang context.
How You Will Benefit
(I) Insights, and validations about the following topics:
Chapter 1: Multilayer Perceptron
Chapter 2: Artificial Neural Network
Chapter 3: Perceptron
Chapter 4: Artificial Neuron
Chapter 5: Activation Function
Chapter 6: Backpropagation
Chapter 7: Delta Rule
Chapter 8: Feedforward Neural Network
Chapter 9: Universal Approximation Theorem
Chapter 10: Mathematics of Artificial Neural Networks
(II) Answering the public top questions about multilayer perceptron.
(III) Real world examples for the usage of multilayer perceptron in many fields.
Who This Book Is For
Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of multilayer perceptron.
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