Application of differentiations in neural networks
Differential calculus is an important tool in machine learning algorithms. Neural networks in particular, the gradient descent algorithm depends on the gradient, which is a quantity computed by differentiation.
In this tutorial, we will see how the back-propagation technique is used in finding the gradients in neural networks.
After completing this tutorial, you will know
- What is a total differential and total derivative
- How to compute the total derivatives in neural networks
- How back-propagation helped in computing the total derivatives
Let’s get started
Tutorial overview
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