Artificial Neural Networks

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Prasad Kharkar is a java enthusiast and always keen to explore and learn java technologies. He is SCJP,OCPWCD, OCEJPAD and aspires to be java architect.

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Hello all, welcome to another tutorial on machine learning. We learned about the role of a neuron in deep learning. In this article, we will understand how artificial neural networks work.

Artificial Neural Networks:

First of all, let us first review  our multiple linear regression model. We used it to predict salary of an employee based on hours worked, certifications and years of experience by simply applying a regressor on input variables.


We did not involve any intermediate layers between input variables and output variable. However, we can increase accuracy of results by using artificial neural networks.


Neural Networks

Neural Networks

  • Note that input layer consists of independent variables worked hours, certifications and experience
  • Now, instead of directly predicting salary, we are feeding input variables to a layer of neurons. They can perform certain operations on input values and pass them on to another layer of neurons.
  • Second layer of neurons again performs some operations on output values from first layer.
  • Output from second layer of neurons is passed on as final prediction.

This was a very short article just to show hidden layers and artificial neural network.


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