Package: sklearn-plus
============Sklearn Plus============.. image:: https://img.shields.io/pypi/v/sklearn_plus.svg:target: https://pypi.python.org/pypi/sklearn_plus.. image:: https://api.travis-ci.org/ybbaigo/sklearn-plus.svg:target: https://travis-ci.org/ybbaigo/sklearn_plus.. image:: https://readthedocs.org/projects/sklearn-plus/badge/?version=latest:target: https://sklearn-plus.readthedocs.io/en/latest/?badge=latest:alt: Documentation StatusA set of python modules for Natural Language Processing* Free software: MIT license* Documentation: https://sklearn-plus.readthedocs.io.Sklearn plus----------------Sklearn plus is an end-to-end neural network API, written in Python. Currently we focus on Natural Language Processing(NLP) tasks. It is based on Tensoflow_ and scikit-learn_. It assembles many preprocessing function, utils and deep learning models about NLP tasks.It was developed with a focus on expanding sklearn and making using deep learning model to handle NLP tasks easier.Features----------------**End-To-End**. Sklearn plus is based on Tensorflow and implements many classical models. Also it offers easy and consistent API with sklearn style for specific NLP task.**Easy extensibility**. Sklearn plus inherits sklearn base classes and follows sklearn API design principles. It is easy to assemble new models, preprocessing functions and utils in it... _Tensoflow: https://www.tensorflow.org/.. _scikit-learn: http://scikit-learn.org/stable/Quick Start----------------* TODOInstallation----------------There are two ways to install Sklearn plus:1. **Install sklearn plus from PyPI(recommended)**:::sudo pip install sklearn-plusIf you are using a virtualenv, you may want to avoid using sudo:::pip install sklearn-plus2. **Install sklearn plus from the GitHub source:**::git clone https://github.com/ybbaigo/sklearn-plus.gitcd sklearn-plussudo python setup.py installContributing pull requests--------------------------------Here's a quick guide to submitting your improvements:1. **Write the code.** There are three base modules in sklearn plus: preprocess, utils and nerual_network. Write your code in the three modules and reference to the samples in them. We use PEP8 syntax conventions.2. **Write the docstrings.** Make sure any code you touch still has up-to-date docstrings and documentation. Please follow the numpydoc_style_.3. **Write tests.** Your code should have full unit test coverage. If you want to see your PR merged promptly, this is crucial.4. **Make sure all tests are passing.** Make sure your code tests can pass on Python 2.7 and Python 3.6 with Tensorflow 1.1.0.5. **Make sure that your PR does not add PEP8 violations.** Make sure that your PR does not add PEP8 violations you can check it by flake8_:* install flake8: ```pip install flake8```* check: ```flake8 path/to/code/```6. **Commit, use appropriate, descriptive commit messages.**7. **Submit your PR.** If you have complete (and passing) unit tests as well as proper docstrings/documentation, your PR is likely to be merged promptly... _numpydoc_style: https://numpydoc.readthedocs.io/en/latest/format.html#overview.. _flake8: http://flake8.pycqa.org/en/latest/index.html#quickstart)Credits-------This package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template... _Cookiecutter: https://github.com/audreyr/cookiecutter.. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage