Explainr AI on Instagram: "🧠 Why Neural Networks Crush Linear Models Imagine a dataset with 2 classes that can’t be separated by a straight line. In such cases, models like logistic regression or linear SVMs struggle to draw an accurate boundary. That’s where neural networks come in — thanks to nonlinear activation functions like ReLU, sigmoid, and tanh. These functions allow networks to stack multiple layers and transform the input space in complex ways. Without these activations, even a deep