Why are two Conv1D layers with different parameters used? #2
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geniuszly
eldar4ikyt
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Please tell me why this happens, why 2 layers are needed |
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Answered by
geniuszly
Oct 9, 2024
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Hello! Using multiple convolutional layers with different filters and kernel sizes helps the model extract more complex and multi-level dependencies in time series data. The first layer processes simpler patterns, while the second layer focuses on more complex connections. |
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Hello! Using multiple convolutional layers with different filters and kernel sizes helps the model extract more complex and multi-level dependencies in time series data. The first layer processes simpler patterns, while the second layer focuses on more complex connections.