WHAT IS NEURAL NETWORK?
Neural networks are also known as artificial neural networks (ANN). We are all familiar with the latest technologies of this era which are machine learning and artificial intelligence. These two technologies are used for making the machines work as human beings. To make a machine act and work like a human being, that machine needs to think like a human being. How can we do that? This is done with the help of neural networks. Neural networks make the machines capable enough to act and think like a human being. The neural networks are not the only solution which is used for the same task. There are many other technologies. But it has been said that neural networks are more effective as compared to other techniques. Neural networks are majorly used for making clusters of the data and for classifying the data.
HOW A NEURAL NETWORK IS MADE?
The whole neural network is made up of neurons. It is said that neurons are the building blocks of the neural network. Neurons are nothing but substances which behave and function like the neurons, which are present in a human body. Apart from neurons, neural networks use a function which is known as a sigmoid function. The sigmoid function is used when we express a derivative in the terms of f (x).
HOW ARE NEURONS CONNECTED IN THE NETWORK?
Neurons are connected in the form of layers. These layers are present over each other, such that one layer can easily communicate with the other. All layers together form a neural network. There are three types of layers in a neural network. They are listed below-->
· Input layer
· Output layer
· Hidden Layer
Those layers which are not considered as input or output layers come under the category of hidden layers. In a neural network, the output of one layer acts as an input for the second layer.
Layers are one of the reasons for the complexity of neural networks. Neurons are present in some amount in the layers. The complexity of a neural network depends on the number of neurons present in the layers. If a greater number of neurons are present, then the complexity would be more. Moreover, a greater number of neurons in the layer can decrease the accuracy of the output.
WHAT IS DEEP NEURAL NETWORK?
When in a neural network, two or more hidden layers are present and each layer has a greater number of neurons or units, then that network is called a deep neural network. There is a technique which is majorly used in machine learning that is deep learning. The deep learning has evolved because of the deep neural networks.
APPLICATIONS OF NEURAL NETWORK
Here are some applications of the neural network which are listed below-->
· Image recognition
· Forecasting
· Character recognition, etc.
CONCLUSION
Neural networks are a very fascinating concept of data science technology. Those who are interested in learning more about data science course can visit here.
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