Using Autograd in PyTorch to Solve a Regression Problem
We usually use PyTorch to build a neural network. However, PyTorch can do more than this. Because PyTorch is also a tensor library with automatic differentiation capability, you can easily use it to solve a numerical optimization problem with gradient descent. In this post, you will learn how PyTorch’s automatic differentiation engine, autograd, works.
After finishing this tutorial, you will learn:
- What is autograd in PyTorch
- How to make use of autograd and an optimizer to solve an optimization problem
Kick-start your project with my book Deep Learning with PyTorch. It provides self-study tutorials with working code.
Let’s get started.
