FT Transformer applied to sequential tabular data
Project description
sequential_ft_transformer
FT Transformer applied to sequential tabular data
Installation
$ pip install sequential_ft_transformer
Usage
- TODO
Contributing
Interested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.
License
sequential_ft_transformer
was created by Christian Orr. It is licensed under the terms of the MIT license.
Credits
sequential_ft_transformer
was created with cookiecutter
and the py-pkgs-cookiecutter
template.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Close
Hashes for sequential_ft_transformer-0.2.0.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | aebf6d1d020b50617c95430fe67c085a62e5e452f409c6dd055bb0fe49f55333 |
|
MD5 | 12140e9b2a8b99a37f6d982d3bf40585 |
|
BLAKE2b-256 | e68ec3b9e93035329347c53540d2b4b4a0148886fbeaca596f97b228200c15d9 |
Close
Hashes for sequential_ft_transformer-0.2.0-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 4f868e816aae29ee2e61511fe2fc0a714e3c33f90036b297ba59785352229d59 |
|
MD5 | 3988660aaa373d6ca333c0c1119196e2 |
|
BLAKE2b-256 | c2cab6fd732599926022cc80075ec7e2eec464d627190a65e170e273bd9e2e84 |