Making Predictions with Multilinear Regression in PyTorch
The multilinear regression model is a supervised learning algorithm that can be used to predict the target variable y given multiple input variables x. It is a linear regression problem where more than one input variables x or features are used to predict the target variable y. A typical use case of this algorithm is predicting the price of a house given its size, number of rooms, and age.
In previous tutorials, we focused on simple linear regression where we used only a single variable x to predict the target variable y. From here on we’ll be working with multiple input variables for prediction. While this tutorial only focuses on a single output prediction y from multiple input variables