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A Quick Guide to AI Neural Network

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A <strong>Quick</strong> <strong>Guide</strong> <strong>to</strong> <strong>AI</strong><br />

<strong>Neural</strong> <strong>Network</strong>


Many things computers do better than humans. But<br />

there are many things that our brains do better than<br />

computers. They have common sense, inspire better and<br />

can imagine<br />

The artificial neural networks are an answer <strong>to</strong> make the<br />

computers more humane and help the machines reason<br />

more like humans.<br />

So What Are They?<br />

Human brains are capable of understanding real-world<br />

situations which computers can’t. The neural networks<br />

came in<strong>to</strong> existence in the 1950s <strong>to</strong> take care of this<br />

issue. The artificial neural network is an attempt <strong>to</strong><br />

simulate the work of neurons which make the human<br />

brain. It allows computers <strong>to</strong> learn things and make<br />

decisions in a humanlike manner. The ANNs are created<br />

by regular programming computers <strong>to</strong> behave as if they<br />

are interconnected brain cells.


How Do They Work?<br />

The <strong>AI</strong> neural networks make use of different layers of<br />

mathematical processing <strong>to</strong> make sense of the<br />

information when it is fed. The artificial neural networks<br />

have dozens of millions of artificial neural network that<br />

are called units which are arranged in the layers.<br />

The input layer gets information from the external world.<br />

It is the data that the network aims <strong>to</strong> process or learn<br />

about. Form the input unit; the data goes through one or<br />

more hidden units. It is the job of the hidden unit <strong>to</strong><br />

transform the input in<strong>to</strong> something the output unit can<br />

use.<br />

The neural networks are fully connected from one layer<br />

<strong>to</strong> the other, and these connections are weighted. When<br />

the weight number is high, one unit has more influence<br />

on the other very much like our brain. When the data<br />

goes through each unit, the network learns more about<br />

each data.


The output units are on the other side, and it is where<br />

the network responds <strong>to</strong> the data which is given and the<br />

processed.<br />

What Are They Used For?<br />

They can be used in many ways so you can find them<br />

being used in classifying the information, predicting the<br />

outcomes, and also creating a cluster of data. The<br />

networks processes and learns from the data as they can<br />

classify the given set of data in<strong>to</strong> the predefined class.<br />

Finally,<br />

There are many Au<strong>to</strong> ML <strong>AI</strong> neural network solutions<br />

available in the market, and you will not even use an <strong>AI</strong><br />

background <strong>to</strong> use them.

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