What is an artificial neural network used for?#
Instead of being programmed with rules, a neural network learns them directly from data examples, allowing it to automate complex pattern-recognition tasks that were previously too difficult for humans to determine the rules of.
How does an artificial neural network work?#
A neural network is organized into layers of interconnected processing units, called nodes. When data is fed into the first layer, each node processes a small piece of information and passes its result to the nodes in the next layer. This continues through all the layers until a final output is produced, such as a prediction or a classification.
The network learns through a process called "training." During training, it is given large sets of data that include the correct answers (e.g., thousands of financial transactions labelled as "fraudulent" or "legitimate"). The network makes a prediction, compares its prediction to the correct answer, and then automatically adjusts the strength of the connections between its nodes to make its next prediction more accurate. This process is repeated millions of times until the network becomes highly effective at the specific task.
How is an artificial neural network different from coded rules?#
An artificial neural network learns rules and patterns directly from data, rather than being explicitly programmed with them. In traditional software development, a human programmer must write precise, step-by-step instructions for the computer to follow. In contrast, you provide a neural network with a large dataset of examples, and it discovers the relevant patterns and logic on its own.