In this chapter, we became familiar with the main concepts of NLP and started to get hands-on with Spark, exploring two potentially useful libraries, spark-corenlp and spark-nlp.
In the next chapter, we will see how it is possible to achieve the same or better results by implementing complex NLP scenarios in Spark though DL (mostly RNN-based). We will explore different implementations by using DL4J, TensorFlow, Keras, the TensorFlow backend, and DL4J + Keras model imports.