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.
Convolutional neural networks
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