tf.keras.layers.normalization - Python for Integrated Circuits - - An Online Book - |
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Python for Integrated Circuits http://www.globalsino.com/ICs/ | ||||||||
Chapter/Index: Introduction | A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W | X | Y | Z | Appendix | ||||||||
================================================================================= Some preprocessing layers have an internal state that can be computed based on a sample of the training data. The stateful preprocessing layers are: The keras modules which are needed for Model.ipynb and required to quickly implement high-performance neural networks
with the TensorFlow backend, are: For each of the Numeric features, a Normalization() layer is used to ensure that the mean of each feature is 0 and its standard deviation is 1. ============================================
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