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In this series of articles, we will explore the world of neural networks and how they work.
In this article, we will discuss the fundamental idea of neural networks.
What is a Neural Network?
A neural network is a computational model that is inspired by the structure and function of the human brain.
It is widely used in many fields like image recognition, natural language processing, etc.
It is most popular machine learning algorithm.
Simplest image of a Neural Network is :
What Neural Networks Manily Do?
It tries to approximate the function of the given input and map it to the output.
In simple terms, it tries to learn the relationship between the input and output. It approximates the output based on the input data.
This will be be done with basic mathematical functions which totaly changes based on the data we provided.
For example:
Let's take example of Drug which can cure illness.
Now let's split the gruop of people based on dosage of drug they consume.
- Low dosage: Group A
- Medium dosage: Group B
- High dosage: Group C
Most Commonly Gruop results may be ploted as this in the graph.
To predict the efficacy of the dosage of drug we can't simply use simple straight line or normal distribution.
As for example I ploted this graph for understaning on how it is done.
This is where nerual network will help.
If we have data points in different location it will find and draw a line to predict the values between the points.
By above graph we can able to understand what neural network can do.
Conclusion
Neural Network is the best tool to fit the data points which are scattered with curve which we can use it to predict the values in between the data points.
We got to know with basic example what it actualy do.
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