Step-by-step solutions with machine learning context
Integrals are used to calculate gradients in backpropagation, the core of how neural networks learn.
Probability distributions (Gaussian, exponential) are defined using integrals - fundamental to Bayesian ML.
Loss functions and gradient descent rely on calculus and integration for finding optimal parameters.
Fourier transforms (used in CNNs) are based on integrals of trigonometric functions.