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Deep learning utility library for natural language processing that aids in feature engineering and embedding layers.

Project description

DeepZensols Natural Language Processing

PyPI Python 3.7 Python 3.8 Python 3.9

Deep learning utility library for natural language processing that aids in feature engineering and embedding layers (see the full documentation).

Features:

  • Configurable layers with little to no need to write code.
  • Natural language specific layers:
  • NLP specific vectorizers that generate zensols deeplearn encoded and decoded batched tensors for spaCy parsed features, dependency tree features, overlapping text features and others.
  • Easily swapable during runtime embedded layers as batched tensors and other linguistic vectorized features.
  • Support for token, document and embedding level vectorized features.
  • Transformer word piece to linguistic token mapping.
  • Two full documented examples provided as both command line and Jupyter notebooks.
  • Command line support for training, testing, debugging, and creating predictions.

Documentation

See the full documentation.

Obtaining

The easiest way to install the command line program is via the pip installer:

pip3 install zensols.deepnlp

Binaries are also available on pypi.

Usage and Examples

If you're in a rush, you can dive right in to the Movie Review Sentiment example, which is a working project that uses this library. However, you'll either end up reading up on the zensols deeplearn library before or during the tutorial.

The usage of this library is explained in terms of two examples:

Attribution

This project, or example code, uses:

Corpora used include:

Changelog

An extensive changelog is available here.

License

MIT License

Copyright (c) 2020 - 2021 Paul Landes

Project details


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