Neural Network

A Neural Network, also called an Artificial Neural Network, is a computational model loosely inspired by biological neurons in the human brain. It consists of interconnected computational units linked by Weighted Connections, often organized into an Input Layer, zero or more Hidden Layers, and an Output Layer. Neural networks underpin Deep Learning, but not all are deep: Deep Neural Networks generally have multiple hidden layers. Computational units typically combine weighted inputs and apply an Activation Function, such as ReLU or Sigmoid, to produce outputs. During training, connection weights are adjusted to learn patterns from data, commonly using Backpropagation to compute Gradients and an optimization method such as Gradient Descent to minimize a Loss Function. Specialized architectures include Convolutional Neural Networks, widely used in Computer Vision, and Transformers, widely used in Natural Language Processing and other domains. Modern advances have been supported by hardware and research contributions from companies such as NVIDIA, whose Graphics Processing Units accelerate neural network computation, and research organizations such as OpenAI and Google DeepMind.