A Gentle Introduction to Multivariate Calculus
It is often desirable to study functions that depend on many variables.
Multivariate calculus provides us with the tools to do so by extending the concepts that we find in calculus, such as the computation of the rate of change, to multiple variables. It plays an essential role in the process of training a neural network, where the gradient is used extensively to update the model parameters.
In this tutorial, you will discover a gentle introduction to multivariate calculus.
After completing this tutorial, you will know:
- A multivariate function depends on several input variables to produce an output.
- The gradient of a multivariate function is computed by finding the derivative of