Perceptrons

What Is Perceptrons

The perceptron is a technique for supervised learning of binary classifiers that is used in the field of machine learning. A function known as a binary classifier is one that can determine whether or not an input, which is often portrayed by a vector of numbers, is a member of a particular category. It is a kind of linear classifier, which means that it is a classification method that forms its predictions on the basis of a linear predictor function by combining a set of weights with the feature vector. In other words, it creates its predictions based on a linear predictor function.

How You Will Benefit

(I) Insights, and validations about the following topics:

Chapter 1: Perceptron

Chapter 2: Supervised learning

Chapter 3: Support vector machine

Chapter 4: Linear classifier

Chapter 5: Pattern recognition

Chapter 6: Artificial neuron

Chapter 7: Hopfield network

Chapter 8: Backpropagation

Chapter 9: Feedforward neural network

Chapter 10: Multilayer perceptron

(II) Answering the public top questions about perceptrons.

(III) Real world examples for the usage of perceptrons 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 perceptrons.

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