Neural Network In Artificial Intelligence What is a neural network in simple terms? An artificial neural network can be called a system of hardware and software that is framed after how neurons in the human brain function. Artificial neural networks are the other name for neural networks. Our brain has billions of neurons, and they are all interconnected. Neural networks contain three major layers: the input layer, the output layer, and a hidden layer. Let us define neural networks first: an artificial intelligence technique called a neural network instructs computers to analyze data in a manner modeled after the human brain. Deep learning is a sort of machine learning that employs interconnected neurons or nodes in a layered framework to mimic the human brain's functions. Like that of the human brain, in a neural network, a neuron is a mathematical function that gathers and categorizes data following a particular architecture. The network is similar to statistical techniques like regression analysis and curve fitting. So far, we have a comfortable understanding of artificial neural networks. First, we will understand the feedforward network. The feedforward networks are made up of hidden layers and several neurons connected by hidden connections. Since there is no backward propagation and the data only travels in one direction, these are referred to as feedforward systems. Convolutional neural network (CNN) is a neural network for deep learning that learns directly from given data. It is used to recognize the given patterns, objects, and faces. Convolutional neural networks are the most popular for image classification. Multiple convolutional layers of CNN are in charge of extracting significant features from the image. Next, we will understand recurrent neural networks (RNNs). When predictions based on sequential data are required, recurrent neural networks come into play. A series of words, images, or other data types might be considered sequential. Multi-layer perceptron (MLP) is a complex architecture of neural networks. Like the human brain, a multi-layered perceptron is made up of linked neurons communicating with a value assigned to every neuron. Three basic layers make up the network: perceptrons with numerous hidden layers and activation mechanisms are known as multi-layer perceptrons. Gradient descent is used to update the weights during the relearning process, which is conducted under supervision. These are all the important types of neural networks. Role of neural networks in medical care: Oncology uses artificial neural networks to train algorithms that can detect malignant tissues at the microscopic level with the same accuracy as skilled medical professionals. Using facial analysis on the images of patients, certain rare diseases that can appear physically can be detected in their earlier stages. Therefore, the widespread adoption of artificial neural networks in healthcare can only increase the diagnostic skills of healthcare professionals and, in the long run, the standard of healthcare globally. Coming to sales and marketing: Based on your previous browsing history, e-commerce sites like Amazon and Flipkart suggest products when you log in, similar to how Zomato, Swiggy, etc., will present restaurant suggestions based on your preferences and previous order history. If you love pasta, it is done using individualized marketing, which is true across all new marketing categories, including book sites, movie services, hospitality sites, etc. Next, we will understand social media. The "People You May Know" tone on Facebook advises users to make friend requests based on potential acquaintances. The individuals you could know are determined by employing artificial neural networks, which examine your profile, interests, existing friends, their friends, and several other characteristics to determine who you might know. Facial recognition is a typical use of machine learning in social media. Convolutional neural networks locate approximately 100 reference points on the subject's face and then compare them to points already present in the database. Next is personal assistants. You all have probably heard of Siri, Alexa, Cortana, and other virtual assistants thanks to your smartphones. These personal assistants employ speech recognition and natural language processing to converse with their users and create responses in line with their needs. Artificial neural networks are used in natural language processing to manage many of these personal assistant functions, including language syntax, semantics, accurate pronunciation, ongoing conversation, etc.