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Artificial Neural Networks/Neural Network Basics

Artificial Neural Networks, also known as “Artificial neural nets”, “neural nets”, or ANN for short, are a computational tool modeled on the interconnection of the neuron in the nervous systems of the human brain and that of other organisms.

Artificial neural networks are very different from biological networks, although many of the concepts and characteristics of biological systems are faithfully reproduced in the artificial systems. Artificial

neural nets are a type of non-linear processing system that is ideally suited for a wide range of tasks, especially tasks where there is no existing algorithm for task completion.

With proper training, ANN are capable of generalization, the ability to recognize similarities among different input patterns, especially patterns that have been corrupted by noise.

Each neuron is a multiple-input, multiple-output (MIMO) system that receives signals from the inputs, produces a resultant signal, and transmits that signal to all outputs.

Soft Computing Lecture 4 Biological Neural Network in ai

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Simplest explanation of Artificial Neural Network in Hindi.

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Artificial Neural Networks Explained !

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Neuron structure / working of Neuron/ biological neural network

Neural Networks, A Simple Explanation

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Lecture 4 | Introduction to Neural Networks

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