2 docs tagged with "gradient"

Mastering the Chain Rule, the fundamental calculus tool for differentiating composite functions, and its direct application in the Backpropagation algorithm for training neural networks.

Defining partial derivatives, how they are calculated in multi-variable functions (like the Loss Function), and their role in creating the Gradient vector for optimization.