Natural Language Processing Best Practices & Examples
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README.md

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NLP Best Practices

This repository contains examples and best practices for building NLP systems, provided as Jupyter notebooks and utility functions. The focus of the repository is on state-of-the-art methods and common scenarios that are popular among researchers and practitioners working on problems involving text and language.

The following section includes a list of the available scenarios. Each scenario is demonstrated in one or more Jupyter notebook examples that make use of the core code base of models and utilities.

Scenarios

Scenario Applications Languages Models
Text Classification Topic Classification en, zh, ar BERT
Named Entity Recognition Wikipedia NER en, zh BERT
Sentence Similarity STS Benchmark en Representation: TF-IDF, Word Embeddings, Doc Embeddings
Metrics: Cosine Similarity, Word Mover's Distance
Embeddings Custom Embeddings Training en Word2Vec
fastText
GloVe

Planning

All feature planning is done via projects, milestones, and issues in this repository.

Getting Started

To get started, navigate to the Setup Guide, where you'll find instructions on how to setup your environment and dependencies.

Contributing

This project welcomes contributions and suggestions. Before contributing, please see our contribution guidelines.