What is Neural Network in ML?
Basic Concepts, Understanding and some applications of Neural Network.
A Neural Network is a method in artificial intelligence that teaches computers to process data in a way that is inspired by the human brain.
It is a type of machine learning process, called Deep Learning, that uses interconnected nodes or neurons in a layered structure that resembles the human brain.
Neural networks reflect the behavior of the human brain, allowing computer programs to recognize patterns and solve common problems in the fields of AI, Machine Learning, and Deep Learning.
Neural network has the following structure, and the components of artificial neural networks which make the fundamentals of neural networks are:
The layer that accepts the information in the form of data.
This hidden layer performs calculations based on the information provided in the input layer and does find data to locate patterns like color, size, etc.
This layer generates the output based on the performance of the input layer and the hidden layer.
Weights and Bias
The input layer consists of the inputs or the independent X variable known as the predictors. These inputs are collected from external sources such as text data, images, audio, or video files. In a natural network, these Xs are the information perceived from the sense organs.
The output layer results from the neural network; it could be a numerical value in a regression problem or a binary or multi-layer class for a classification problem. The output can also be the recognition of handwriting or audio voice or classified image or text in categories.
Apart from the Input and the Output layer, there is another layer in the Neural Networks, called the Hidden Layer, which derives the features for the model.
Single Layer Perceptron: The neural net with one single hidden layer is called the Single Layer Perceptron.
Multilayer Perceptron: The neural net with more than one hidden layer and where each of the layers is connected is called the Multilayer Perceptron.
Some Applications of Neural Network
The neural network has a lot of applications that companies, Industries, and even we are using. It is currently the most popular topic in the field of Artificial Intelligence.
1. Speech Processing
Another function of an artificial neural network is speech processing. Each of us has used the Translator app. Simply provide your speech, and the translator will turn it into text. Text to speech is also used on occasion. Another well-known example is speech recognition.
2. Image Processing
Face recognition is an app that is available on every smartphone. This method of image processing is also employed for face recognition. It looks for a face in the image provided as data.
3. Stock Market Prediction
An artificial neural network enables speedy analysis of a large amount of data and forecasted.