Skip to main content

Python library that integrates with neo4j facilitating in fraud detection using deep learning techniques.

Project description

Python Library that integrates with neo4j and aims to make the process of fraud detection using knowledge graphs easier.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

pyNeFrauds-0.0.1-py3-none-any.whl (14.2 kB view details)

Uploaded Python 3

File details

Details for the file pyNeFrauds-0.0.1-py3-none-any.whl.

File metadata

  • Download URL: pyNeFrauds-0.0.1-py3-none-any.whl
  • Upload date:
  • Size: 14.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.4.2 requests/2.28.1 setuptools/45.2.0 requests-toolbelt/0.10.1 tqdm/4.64.0 CPython/3.8.10

File hashes

Hashes for pyNeFrauds-0.0.1-py3-none-any.whl
Algorithm Hash digest
SHA256 78c20480c5265b915a13c624189d123160352a8b6b2a5a6e3180da232104ffac
MD5 c900136ea2e081e4a948162a6f0f0b42
BLAKE2b-256 7e65bdf09044a3b802a89f08463d9ef1c530048cbfac0c420f07c00c9afbca73

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page