Update README.md
Signed-off-by: David Rotermund <54365609+davrot@users.noreply.github.com>
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Parameters for the layers:
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[padding](https://www.tensorflow.org/api_docs/python/tf/keras/layers/Conv1D): "One of "valid", "same" or "causal" (case-insensitive). "valid" means no padding. "same" results in padding with zeros evenly to the left/right or up/down of the input such that output has the same height/width dimension as the input. "causal" results in causal (dilated) convolutions, e.g. output[t] does not depend on input[t+1:]. "
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[use_bias](https://www.tensorflow.org/api_docs/python/tf/keras/layers/Conv1D): "Boolean, whether the layer uses a bias vector."
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[activation](https://www.tensorflow.org/api_docs/python/tf/keras/layers/Conv1D): "Activation function to use. If you don't specify anything, no activation is applied (see [keras.activations](https://www.tensorflow.org/api_docs/python/tf/keras/activations))."
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[data_format](https://www.tensorflow.org/api_docs/python/tf/keras/layers/Conv1D): " A string, one of channels_last (default) or channels_first."
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|[padding](https://www.tensorflow.org/api_docs/python/tf/keras/layers/Conv1D) | "One of "valid", "same" or "causal" (case-insensitive). "valid" means no padding. "same" results in padding with zeros evenly to the left/right or up/down of the input such that output has the same height/width dimension as the input. "causal" results in causal (dilated) convolutions, e.g. output[t] does not depend on input[t+1:]. "|
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|[use_bias](https://www.tensorflow.org/api_docs/python/tf/keras/layers/Conv1D)| "Boolean, whether the layer uses a bias vector."|
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|[activation](https://www.tensorflow.org/api_docs/python/tf/keras/layers/Conv1D)| "Activation function to use. If you don't specify anything, no activation is applied (see [keras.activations](https://www.tensorflow.org/api_docs/python/tf/keras/activations))."|
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[data_format](https://www.tensorflow.org/api_docs/python/tf/keras/layers/Conv1D)| " A string, one of channels_last (default) or channels_first."|
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```python
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from tensorflow import keras
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