A machine learning library for economics and finance
Project description
Welcome to gingado!
A machine learning library for economics and finance
gingado
seeks to facilitate the use of machine learning in economic and finance use cases, while promoting good practices. gingado
aims to be suitable for beginners and advanced users alike.
Overview
gingado
is a free, open source library built around three main functionalities:
- data augmentation, to add more data from official sources, improving the machine models being trained by the user;
- automatic benchmark model, to enable the user to assess their models against a reasonably well-performant model; and
- support for model documentation, to embed documentation and ethical considerations in the model development phase.
Each of these functionalities builds on top of the previous one. They can be used on a stand-alone basis, together, or even as part of a larger pipeline from data input to model training to documentation!
Design principles
The choices made during development of gingado
derive from the following principles, in no particular order:
- lowering the barrier to use machine learning can help more economists familiarise themselves with these techniques and use them when appopriate
- offering compatibility with other existing software that is consolidated by wide practice benefits users and should be promoted as much as possible
- promoting good practices such as documenting ethical considerations and benchmarking models as part of machine learning development will help embed these habits in economists
Presentations, talks, papers
The material supporting public communication about gingado
(ie, slide decks, papers) is kept in this dedicated repository. Interested users are welcome to visit the repository and comment on the drafts or slide decks, preferably by opening an issue. I also store in this repository suggestions I receive as issues, so users can see what others commented (anonymously unless requested) and comment along as well!
Install
To install gingado
, simply run the following code on the terminal:
$ pip install gingado
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