Question

Write a short note on neural networks

Answer 1

Neural Networks are collections of Neurons containing specific algorithms which are networked together to solve a particular set of problems irrespective of data size.

How Neural Networks (NN) works?

In the above image as we can see that the Neural Networks is divided into 3 components.

1. In the first layer of Neural Networks, there is input data in which we insert data.
2. In the second layer of Neural Networks, there are multiple hidden layers are there which are not visible but all processing occurs in these layers.
3. In the third layer of Neural Networks, there is output data which gives the output of data that was processed in the hidden layers.

How Neural Networks(NN) learn 

There are three ways neural networks Learn.

1. Supervised Learning is where a computer algorithm is trained on input data that has been labeled for a particular output.
2. Unsupervised Learning is in which a system learns through data sets created on its own. In unsupervised is not labeled.
3. Reinforcement Learning Learning through feedback or trial and error method is called Reinforcement Learning.

Features of Neural Networks(NN)

• Neural Networks(NN) systems are modeled on the functioning of the human brain
• They are able to automatically extract features without input from the programmer
• Every neural network is essentially a machine learning algorithm
• It is useful when solving problems for which the data set is very large

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Learn More about Neural Networks at - Neural Network Class 9