A neural network is a specific kind of machine learning or artificial intelligence (AI) that involves training a computer to recognize specific patterns or features in data. In the case of bird identification, a neural network is trained using a vast dataset comprising thousands of accurately labeled bird sounds. This dataset serves as a teaching tool, enabling the computer to learn and distinguish individual bird calls and songs.

Similar to how we teach a toddler the meaning of a word like "dog," the neural network learns through exposure to numerous examples and guided instruction. In the early stages, caregivers provide guidance by associating the word "dog" with actual dogs and reinforcing the concept through positive reinforcement ("That's a dog. What a nice dog!"). As the child encounters new animals, they start to apply their understanding and ask questions like "Dog?" to seek confirmation ("No honey, that's a cat.") or receive positive feedback ("Yes! What a beautiful dog!").

Similarly, the neural network progressively refines its ability to identify new bird sounds it hasn't encountered before, drawing on its extensive training with labeled examples. Through this iterative learning process, the computer becomes highly proficient at recognizing and classifying unfamiliar bird vocalizations.