Practical Time Series Analysis

Convolutional neural networks

This section describes Convolutional Neural Networks (CNNs) that are primarily applied to develop supervised and unsupervised models when the input data are images. In general, two-dimensional (2D) convolutions are applied to images but one-dimensional (1D) convolutions can be used on a sequential input to capture time dependencies. This approach is explored in this section to develop time series forecasting models.