How Neural Networks Work – Explained Using the Straight Line Equation y = ax + b

Neural networks rely on the equation y = ax + b, which describes how outputs change when inputs change. The concept progresses from basic linear regression (finding the best line to fit data points) to linear classification (using lines as decision boundaries), then to complex deep neural networks. Deep networks stack multiple layers of these linear calculations while adding non-linear adjustments, enabling them to handle sophisticated problems like image recognition and language translation.