nlp_from_scratch_index.rst

NLP from Scratch

In these three-part series you will build and train a basic character-level Recurrent Neural Network (RNN) to classify words.

You will learn:

• How to construct Recurrent Neural Networks from scratch
• Essential data handling techniques for NLP
• How to train an RNN to identify the language origin of words.

Before you begin, we recommend that you review the following:

• PyTorch Learn the Basics series
• How to install PyTorch

.. grid:: 3

     .. grid-item-card:: :octicon:`file-code;1em`
        NLP From Scratch - Part 1: Classifying Names with a Character-Level RNN
        :link: https://pytorch.org/tutorials/intermediate/char_rnn_classification_tutorial.html
        :link-type: url

        Learn how to use an RNN to classify names into their language of origin.
        +++
        :octicon:`code;1em` Code

     .. grid-item-card:: :octicon:`file-code;1em`
        NLP From Scratch - Part 2: Generating Names with a Character-Level RNN
        :link: https://pytorch.org/tutorials/intermediate/char_rnn_generation_tutorial.html
        :link-type: url

        Expand the RNN we created in Part 1 to generate names from languages.
        +++
        :octicon:`code;1em` Code

     .. grid-item-card:: :octicon:`file-code;1em`
        NLP From Scratch - Part 3: Translation with a Sequence to Sequence Network and Attention
        :link: https://pytorch.org/tutorials/intermediate/seq2seq_translation_tutorial.html
        :link-type: url

        Create a sequence-to-sequence model that can translate your text from French
        to English.
        +++
        :octicon:`code;1em` Code