graykode/nlp-tutorial
Natural Language Processing Tutorial for Deep Learning Researchers
This project helps deep learning researchers and students understand how core Natural Language Processing (NLP) models work. It provides practical examples that take text data as input and demonstrate how to perform tasks like predicting the next word, classifying text sentiment, or translating sentences. Anyone studying deep learning for NLP and wanting to see working examples of algorithms will find this useful.
14,870 stars. No commits in the last 6 months.
Use this if you are a deep learning researcher or student learning NLP and need clear, concise code examples for fundamental algorithms like Word2Vec, BERT, or Transformers.
Not ideal if you are looking for a plug-and-play tool for immediate application development or if you prefer using TensorFlow over PyTorch.
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Jupyter Notebook
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Feb 21, 2024
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