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Generating Text Using TensorFlow

One fun thing we can do with machine learning is generating text! We can build a model that will predict the next word in a sequence. This combines interesting aspects of both sequence processing and natural language processing. This lab will give you more practice in both of these important areas of machine learning. ### Prerequisites This lab is designed to be completed in PyCharm running on your machine. You should have PyCharm and TensorFlow installed before attempting this lab. We will not be covering this setup in the lab.

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Level
Clock icon Advanced
Duration
Clock icon 1h 0m
Published
Clock icon Aug 13, 2021

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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!
A Cloud Guru - Labs - Generating Text Using TensorFlow
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A Cloud Guru

The Cloud Content team comprises subject matter experts hyper focused on services offered by the leading cloud vendors (AWS, GCP, and Azure), as well as cloud-related technologies such as Linux and DevOps. The team is thrilled to share their knowledge to help you build modern tech solutions from the ground up, secure and optimize your environments, and so much more!

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