We can do multiple linear regression on the same data by making a slight modification in the declaration of weights and placeholders. In the case of multiple linear regression, as each feature has different value ranges, normalization becomes essential. Here is the code for multiple linear regression on the Boston house price dataset, using all the 13 input features.