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typo
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samples/core/tutorials/keras/basic_text_classification.ipynb

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"cell_type": "markdown",
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"source": [
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"The layers are stacked sequentially to build the classifer:\n",
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"The layers are stacked sequentially to build the classifier:\n",
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"\n",
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"1. The first layer is an `Embedding` layer. This layer takes the integer-encoded vocabulary and looks up the embedding vector for each word-index. These vectors are learned as the model trains. The vectors add a dimension to the output array. The resulting dimensions are: `(batch, sequence, embedding)`.\n",
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"2. Next, a `GlobalAveragePooling1D` layer returns a fixed-length output vector for each example by averaging over the sequence dimension. This allows the model can handle input of variable length, in the simplest way possible.\n",

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