1 / 4

A Quick Guide to AI Neural Network

The artificial neural network is an attempt to simulate the work of neurons which make the human brain. It allows computers to learn things and make decisions in a human like manner.

femella
Télécharger la présentation

A Quick Guide to AI Neural Network

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. A Quick Guide to AI Neural Network

  2. Many things computers do better than humans. But there are many things that our brains do better than computers. They have common sense, inspire better and can imagine The artificial neural networks are an answer to make the computers more humane and help the machines reason more like humans. So What Are They? Human brains are capable of understanding real-world situations which computers can’t. The neural networks came into existence in the 1950s to take care of this issue. The artificial neural network is an attempt to simulate the work of neurons which make the human brain. It allows computers to learn things and make decisions in a humanlike manner. The ANNs are created by regular programming computers to behave as if they are interconnected brain cells.

  3. How Do They Work? The AI neural networks make use of different layers of mathematical processing to make sense of the information when it is fed. The artificial neural networks have dozens of millions of artificial neural network that are called units which are arranged in the layers. The input layer gets information from the external world. It is the data that the network aims to process or learn about. Form the input unit; the data goes through one or more hidden units. It is the job of the hidden unit to transform the input into something the output unit can use. The neural networks are fully connected from one layer to the other, and these connections are weighted. When the weight number is high, one unit has more influence on the other very much like our brain.

  4. When the data goes through each unit, the network learns more about each data. The output units are on the other side, and it is where the network responds to the data which is given and the processed. What Are They Used For? They can be used in many ways so you can find them being used in classifying the information, predicting the outcomes, and also creating a cluster of data. The networks processes and learns from the data as they can classify the given set of data into the predefined class. Finally, There are many Auto ML AI neural network solutions available in the market, and you will not even use an AI background to use them.

More Related