Deep Learning for Natural Language Processing

8 Multitask learning

This chapter covers

• Understanding deep multitask learning for NLP
• Implementing hard, soft, and mixed parameter sharing for multitask learning

In this chapter, we apply different multitask learning approaches to practical NLP problems. In particular, we apply multitask learning to three datasets:

• Two sentiment datasets consisting of consumer product reviews and restaurant reviews

• The Reuters topic dataset

• A part-of-speech and named-entity tagging dataset

8.1 Introduction to multitask learning

Multitask learning is concerned with learning several things at the same time (figure 8.1). An example is learning both part-of-speech tagging and sentiment analysis simultaneously or learning two topic taggers in one go. Why ...