mindspore-courses/DeepNLP-models-MindSpore

About MindSpore implementations of various Deep NLP models in cs-224n(Stanford Univ)

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Experimental

This project provides practical, runnable examples of various deep learning models specifically designed for natural language processing tasks. It takes raw text data as input and produces outputs like word embeddings, parsed sentences, or classified text, depending on the model. It's for researchers and students in computational linguistics or AI who want to understand and experiment with core NLP algorithms.

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Use this if you are studying or researching Deep Natural Language Processing and want hands-on examples to complement academic lectures like Stanford's CS224n.

Not ideal if you are looking for a plug-and-play solution for an existing business problem without delving into the underlying model architectures.

natural-language-processing computational-linguistics text-mining machine-translation sentiment-analysis
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 6 / 25
Maturity 16 / 25
Community 4 / 25

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Language

Jupyter Notebook

License

Apache-2.0

Last pushed

Oct 09, 2023

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