In this project Shakespeare plays by LiamLarsen is used to create a deep learning model which will be able to generate text using some input text.

While doing all of this we will go through:

• Preprocessing text data
• Building multilayer Bidirectional LSTM model
• Saving wording embeddings learned by the learning algorithm

• Getting started
• Deep learning model performance
• License

This deep learning model is trained using GPU and to work in the same environment having packages with versions which were used while making this notebook, go to Kaggle where the kernel is saved.

In Kaggle kernel you'll find embedding vectors and metadata which can be used to display embedding learned by the model using Tensorflow Projector.

The data is text which has 4,583,798 words but only 500,000 words are used train the model. There is no validation or testing set. This model is trained for 20 epochs.

Model's performance by the last (20th) epoch

Text generated by the model

Word cloud for training text

APACHE LICENSE, VERSION 2.0