Understanding Neural Networks
Published: October 6, 2025
Neural networks are the foundation of modern AI. They’re computational models inspired by the way biological neurons process information. Each “neuron” in a neural network receives inputs, applies weights, and passes an output to the next layer.
At the core of a neural network lies the concept of learning through optimization. Using algorithms like gradient descent, the network adjusts its parameters to minimize prediction errors over time.
In practice, these models power applications like image recognition, chatbots, and recommendation systems. The key takeaway: neural networks are not magic — they’re structured math with feedback and learning.