Project Hadron has been built to bridge the gap between data scientists and data engineers. More specifically between machine learning business outcomes and the final product. It translates the work of data scientists into meaningful, production ready solutions that can be easily managed by product engineers.
The purpose of this project is to hold example code that aligns to the Project Hadron documentation as well as extra examples of its use. The majority of the examples are written using Juypter Notebook but can also be used in an IDE.
These examples require the discovery-transition-ds package to be installed, along with Jupyter or the
IDE of choice.
The best way to install the component packages is directly from the Python Package Index repository using pip.
The component package is discovery-transition-ds and pip installed with:
python -m pip install discovery-transition-dsif you want to upgrade your current version then using pip install upgrade with:
python -m pip install -U discovery-transition-dsThis will also install or update dependent third party packages. The dependencies are limited to python and related Data Science tooling such as pandas, numpy, scipy, scikit-learn and visual packages matplotlib and seaborn, and thus have a limited footprint and non-disruptive in a machine learning environment.
hadron-examples is actively developed on GitHub, where the code is
always available.
You can clone the public repository with:
$ git clone git@github.com:project-hadron/hadron-examples.gitIf you want to contact me you can reach me at gigas64@opengrass.net
This project uses the following license: BSD 3-Clause.