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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 <https://pytorch.org/tutorials/beginner/basics/intro.html>`__ * `How to install PyTorch <https://pytorch.org/get-started/locally/>`__ .. 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