Metadata-Version: 1.1
Name: sng
Version: 0.3.1
Summary: Generate name proposals for companies, software, etc.
Home-page: http://github.com/AlexEngelhardt/startup-name-generator
Author: Alexander Engelhardt
Author-email: alexander.w.engelhardt@gmail.com
License: MIT
Description: startup-name-generator
        ======================
        
        - `This package on PyPI <https://pypi.org/project/sng/>`_
        - `This package on GitHub <https://github.com/AlexEngelhardt/startup-name-generator>`_
        
        Summary
        -------
        
        This package can train a model that learns the "structure" of the words in a
        supplied text corpus. It then generates new words with a similar structure,
        which can be used as suggestions for naming things like companies or software.
        
        Quickstart
        ----------
        
        Check out the `Jupyter Notebook(s) in doc/notebooks/ <https://startup-name-generator.readthedocs.io/en/latest/notebooks/01_quickstart.html>`_.
        
        Documentation
        -------------
        
        - The full documentation is `available online <https://startup-name-generator.readthedocs.io/en/latest/>`_
        - I also gave a lightning talk presenting the basic idea, it's available `on Youtube <https://www.youtube.com/watch?v=1w3Q3CEldG0>`_.
        
        Extended summary
        ----------------
        
        Naming a startup is `hard <https://mashable.com/2012/10/04/startup-naming/>`_.
        
        I therefore wrote a Python package to randomly generate company name ideas.
        
        It takes an arbitrary text as input, and then trains a recurrent neural network
        (RNN) on each its words, learning the structure of the text. The input text can
        be a simple word list (e.g. Greek or Gallic), or a chapter from a book, or just
        a random list of words (e.g. all Pokemon). The script then generates new random
        names that sound simliar to the provided list.
        
        Literature/References
        ---------------------
        
        - `Andrew Ng's Deep Learning MOOC <https://www.deeplearning.ai/>`_
        - http://karpathy.github.io/2015/05/21/rnn-effectiveness/
        - https://github.com/keras-team/keras/blob/master/examples/lstm_text_generation.py
        
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Environment :: Console
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Text Processing :: Linguistic
Classifier: Topic :: Utilities
