Summary: Text Classification with SpaCy
Let's review what we've learned in this section.
We'll cover the following
We have finished discussing a very hot NLP topic—text classification.
Key points
We learned about text classification concepts such as binary classification, multilabel classification, and multiclass classification.
We learned how to train
TextCategorizer
, spaCy's text classifier component.We learned how to transform your data into spaCy training format and then train the
TextCategorizer
component with this data.We learned how to combine spaCy code and Keras code.
We learned the basics of neural networks, including some handy layers such as the dense layer, dropout layer, embedding layer, and recurrent layers.
We learned how to tokenize and preprocess the data with Keras'
Tokenizer
.We went through neural network design with
tf.keras
code and learned how to design and evaluate a statistical experiment with LSTM.
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