typo

samples/core/tutorials/keras/basic_text_classification.ipynb

@@ -512,7 +512,7 @@
       },
       "cell_type": "markdown",
       "source": [
-        "The layers are stacked sequentially to build the classifer:\n",
+        "The layers are stacked sequentially to build the classifier:\n",
         "\n",
         "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",
         "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",