AP Psychology Practice Test 2026 - Free AP Psychology Practice Questions and Study Guide

Computer neural networks perform tasks primarily through learning and recognizing patterns. This process is akin to how the human brain operates, where connections between neurons strengthen or weaken based on experiences and stimuli. In neural networks, data is fed into the system, and through various layers of interconnected nodes (or artificial neurons), the network learns to identify patterns by adjusting the weights of the connections based on the input data.

The learning process often involves techniques such as supervised learning, where the network is trained on labeled datasets, and it fine-tunes itself based on the errors in its predictions. As the network is exposed to more data over time, it becomes better at recognizing patterns and making predictions or classifications based on new input data. This capability to learn from data and improve performance over time distinguishes neural networks from traditional computing methods, which rely on fixed instructions.