Nemoa is a python framework for deep data analysis. In many domains of
statistical data analysis the lack of strong structural beliefs requires deep
structured models to capture the respective uncertainty. These classes of
statistical models, however, are barely accessible by traditional statistical
approaches. The key goal of this project is therefore, to provide an intuitive
framework for deep data analysis, which closes this gap by utilizing methods
from differential geometry and differential topology. The fields of applications
comprise nonlinear association analysis, reconstruction of missing data,
classification tasks and data dimensionality reduction.
Nemoa is available free for any use under the GPLv3 license. For installation instructions see the documentation page.
Contributers are very welcome! Feel free to report bugs and feature requests to the issue tracker provided by GitHub. You can also follow the progress of the project by joining the google group.
Nemoa is maintained by Patrick Michl