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This is a mirror of the official fast.ai course notebook for the Dsnet meetup. Please check the course repo for the latest updates

This notebook was part of Lesson 7 of the Practical Deep Learning for Coders course.

Predicting English word version of numbers using an RNN

We were using RNNs as part of our language model in the previous lesson. Today, we will dive into more details of what RNNs are and how they work. We will do this using the problem of trying to predict the English word version of numbers.

Let's predict what should come next in this sequence:

eight thousand one , eight thousand two , eight thousand three , eight thousand four , eight thousand five , eight thousand six , eight thousand seven , eight thousand eight , eight thousand nine , eight thousand ten , eight thousand eleven , eight thousand twelve...

Jeremy created this synthetic dataset to have a better way to check if things are working, to debug, and to understand what was going on. When experimenting with new ideas, it can be nice to have a smaller dataset to do so, to quickly get a sense of whether your ideas are promising (for other examples, see Imagenette and Imagewoof) This English word numbers will serve as a good dataset for learning about RNNs. Our task today will be to predict which word comes next when counting.

In deep learning, there are 2 types of numbers