Table of Contents

1. Challenge

   Retrieve and Load the Tiny Frankenstein Data

   1. Download the Tiny Frankenstein dataset: https://storage.googleapis.com/acg-datasets/tiny_frankenstein.tgz.
   2. Load the raw text into the program.
   3. Convert the text to lowercase.
2. Challenge

   Turn the Text Data into Token Sequences

   1. Train a tokenizer on the Frankenstein text using every available word.
   2. Find the total number of learned words.
   3. Convert the Frankenstein text to tokens.
   4. Convert the tokens to sequences.
3. Challenge

   Build a Model to Predict Tokens

   1. Create a recurrent neural network to learn the token sequences.
      • Hint: Bidirectional LSTMs work really well for this task!
   2. Compile the model with an appropriate loss function and optimizer.
      • Hint: You might want to increase the learning rate of the optimizer. This model can take a very long time to converge with the default learning rate.
   3. Train your model for 10-20 epochs.
4. Challenge

   Generate Text!

   1. Create a reverse token lookup dictionary from the tokenizer's word_index.
   2. Create tokenized text to start the predictions.
   3. Use the model to predict the next token.
   4. Append the predicted token to the text, truncating earlier values.
   5. Continue using the model to predict as many tokens as you'd like!