What Is a Neural Network? How It Works and Where It's Used

Artificial Neural Network (ANN) is a machine version of the human brain. Human brains can detect and recognize objects or images similar to Neural Network work. How it works and Where it is used will be discussed here.

Neural Network consist of nodes known as “Neurons” that are arranges between layers. Layers are of three types - input layer, hidden layer and output layer. They commonly form a network.

These networks work the same as the human brain to recognize patterns, and make predictions and they learn through experience.

How it works?

For better understanding let’s discuss it with an example - assume we need to identify a dog’s image. Here are the following steps used for the recognition.

1. Input Layer: Just like our eyes take the input for the brain, this layer receives the data which then gets converted into numerical values that represents pixel intensities.
2. Hidden Layer: Just like our nerves carry the information to the brain, this layer passes the information through multiple layers where neurons calculate a weighted sum and apply functions like ReLU or Sigmoid. This layer helps the network understand non-linear patterns.
3. Output Layer: The output layer is the final layer that shows results in the format of probability score indicating the likelihood of image.
4. Learning Process: The network undergoes training through a method called backpropagation. It calculates errors, adjusts weights, and optimizes the model using techniques like Gradient Descent.

Types of Neural Networks

There are several common types of Neural Networks

1. Feedforward Neural Network (FNN)
2. Convolutional Neural Network (CNN)
3. Recurrent Neural Network (RNN)
4. Long Short Term Memory (LSTM)
5. Generative Adversarial Network (GAN)
6. Transform Network

Where we do use Neural Networks?

We use neural networks on a daily basis without being noticed. Prime examples of neural networks are Siri and Google Assistant.

Here a question arises: how? As while using Siri or Google Assistant, we give commands through speech recognition, then models like NLP decode the context and meaning to make it understood by the system, and then a neural network is used to craft replies that sound natural.

Hence, neural networks are an important part of modern AI applications, which can recognize patterns and decision-making. Unsupervised learning is a common thing of ML that uses neural networks.