Dojo

Dojo is a Machine Learning library for Python

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.

Prerequisites

• Python - The Programming Language used.
• Pipenv - Dependency and Virtual Environment Management

Download for Mac OSX using Homebrew

brew install python
brew install pipenv

Installing for development

A step by step series of examples that tell you how to get a development env running

1. Since we are using the Python programming language as a main language, you will need to download it. You can do so from the official Python website.

2. Once you have Python up and running we then need to setup our development env. For that we are using Pipenv. You will need to install it. Check out these instructions to see how is done.

3. Now, that you have the prerequisites the only part left is too install all the other Pyhton packages that Dojo depends on. To do run the following:

   pipenv install --dev
   

   The --dev tag is used in order Pipenv to know to install also the packages that are used in the package development process.

Installing for use

If you plan just to use Dojo as a Machine Learning library you can install it using pip like so:

pip install pydojoml

Running the tests

Coming soon...

Break down into end to end tests

Coming soon...

And coding style tests

Coming soon...

Built With

• NumPy - Fundamental package for scientific computing with Python
• SciPy - Package that provides many user-friendly and efficient numerical routines
• Matplotlib - Python 2D plotting library
• progressbar - Text progress bar library for Python
• terminaltables - Easily draw tables in terminal/console applications

Contributing

Please read CONTRIBUTING.md for details on our code of conduct, and the process for submitting pull requests to us.

Versioning

For the versions available, see the tags on this repository.

Authors

• Victor Velev - Initial work - VIVelev

See also the list of contributors who participated in this project.

License

This project is licensed under the MIT License - see the LICENSE file for details

Acknowledgments

• Eric Jones and Travis Oliphant and Pearu Peterson and others for writing such great packages - the SciPy ecosystem.
• Nilton Volpato for writing progressbar
• Robpol86 for writing terminaltables