Feedforward neural networks for multivariate time series forecasting
In this recipe, we’ll return our attention to deep neural networks. We’ll show you how to build a forecasting model for multivariate time series using a deep feedforward neural network. We’ll describe how to couple the DataModule
class with TimeSeriesDataSet
to encapsulate the data preprocessing steps. We’ll also place the PyTorch
models within a LightningModule
structure, which standardizes the training process of neural networks.
Getting ready
We’ll continue to use the multivariate time series related to solar radiation forecasting:
import pandas as pd mvtseries = pd.read_csv('assets/daily_multivariate_timeseries.csv', parse_dates=['datetime'], ...