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.
What Is Artificial Intelligence Series
The Artificial Intelligence eBook series provides comprehensive coverage in over 200 topics. Each ebook covers a specific Artificial Intelligence topic in depth, written by experts in the field. The series aims to give readers a thorough understanding of the concepts, techniques, history and applications of artificial intelligence. Topics covered include machine learning, deep learning, neural networks, computer vision, natural language processing, robotics, ethics and more. The ebooks are written for professionals, students, and anyone interested in learning about the latest developments in this rapidly advancing field.
The Artificial Intelligence eBook series provides an in-depth yet accessible exploration, from the fundamental concepts to the state-of-the-art research. With over 200 volumes, readers gain a thorough grounding in all aspects of Artificial Intelligence. The ebooks are designed to build knowledge systematically, with later volumes building on the foundations laid by earlier ones. This comprehensive series is an indispensable resource for anyone seeking to develop expertise in artificial intelligence.
