In the previous chapter, we became familiar with the core concepts of Natural Language Processing (NLP) and then we saw some implementation examples in Scala with Apache Spark, and two open source libraries for this framework. We also understood the pros and cons of those solutions. This chapter walks through hands-on examples of NLP use case implementations using DL (Scala and Spark). The following four cases will be covered:
- DL4J
- TensorFlow
- Keras and TensorFlow backend
- DL4J and Keras model import
The chapter covers some considerations regarding the pros and cons for each of those DL approaches in order, so that readers should then be ready to understand in which cases one framework is preferred over the others.
