Types of Neural Networks Used by Artificial Intelligence

Neural Networks used by Artificial Intelligence

Neural Networks are a subset of Machine Learning techniques which learn the data and patterns in a different way. It also utilizes Neurons and Hidden layers. Neural Networks are powerful due to their complex structure and can be used in applications by the students of Best BTech College in Jaipur.

What are Neural Networks?

Neural Networks use the architecture of human neurons with multiple inputs, a processing unit, and single/multiple outputs. There are weights related with each connection of neurons. By adjusting these weights, a neural network arrives at an equation which is used for predicting outputs on new unseen data by the students of engineering colleges in Jaipur. It can be done by backpropagation and updating of the weights.

Various Types of Neural Networks

Different types of neural networks are used by the students of BTech colleges for different data and applications. The different architectures of neural networks are particularly designed to work on those types of data or domain. There are some basic and some complex ones includes the following:

Perceptron

The Perceptron is the most basic form of neural networks. It consists of just 1 neuron which takes the input and applies activation function to produce a binary output. It does not contain any hidden layers and can be further used for binary classification tasks. Additionally, the neuron does the processing of input values with their weights. Then, it passes to the activation function to produce a binary output.

Feed Forward Network ?????

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