Neural networks mimic human brain functions through interconnected layers of nodes or neurons that process information. Each node performs a mathematical operation, and the network learns through adjustments made during training phases, similar to how synapses strengthen with experience in the brain. These networks excel in recognizing patterns, classifying data, and making predictions. By using large datasets and algorithms such as backpropagation, neural networks adapt over time, improving their performance in tasks ranging from image recognition to natural language processing.