Training a linear regression model for forecasting with a multivariate time series

In this recipe, we’ll use PyTorch to train a linear regression model as our first forecasting model fit on a multivariate time series. We’ll show you how to use TimeSeriesDataSet to handle the preprocessing steps for training the model and passing data to it.

Getting ready

We’ll start this recipe with the mvtseries dataset that we used in the previous recipe:

import pandas as pd
mvtseries = pd.read_csv('assets/daily_multivariate_timeseries.csv',
            parse_dates=['datetime'],
            index_col='datetime')

Now, let’s see how we can use this dataset to train a PyTorch model.

How to do it…

In the following code, we’ll describe the necessary steps to prepare the time series and build a linear...