Artificial Neural Networks (ANNs) are computer systems designed to mimic how the human brain processes information . Just like the brain uses neurons to process data and make decisions, ANNs use artificial neurons to analyze data, identify patterns and make predictions. Researchers use Artificial Neural Networks (ANN) algorithms based on brain function to model complicated patterns and forecast issues. The Artificial Neural Network (ANN) is a deep learning method that arose from the concept of the human brain Biological Neural Networks . They are among the most powerful machine learning algorithms used today. Artificial neural network simulate the functions of the neural network of the human brain in a simplified manner. In this TechVidvan Deep learning tutorial, you will get to know about the artificial neural network ’s definition, architecture, working, types, learning techniques, applications, advantages, and disadvantages. An Artificial Neural Network is a computational model inspired by the human brain's structure composed of interconnected nodes organised in layers. A computer system that mimics the information processing of the human brain is called an artificial neural network , or ANN.
