Neural Network

Neural networks are the foundational building blocks of modern AI. They consist of layers of artificial neurons (nodes) connected by weighted edges. Data flows through the network, with each layer learning increasingly abstract representations — from simple patterns in early layers to complex concepts in deeper ones.

Architectures range from simple feedforward networks to convolutional neural networks (CNNs) for images, recurrent neural networks (RNNs) for sequences, and transformers for language. Deep neural networks — those with many layers — give rise to the field of deep learning.

Nearly every AI job involves neural networks at some level. Data scientists and ML engineers design, train, and deploy them. Understanding backpropagation, gradient descent, activation functions, and regularization techniques is foundational knowledge for anyone entering the AI field.