Skip to main content

knowledge representation tools

Project description

Knowledge Embedding Kit

PyPI version fury.io PyPI license Build Status

This library provides helpful functions and sampling for KGE learning. The data processing part is strictly research-oriented.

Requirements:

  • C++17 compilers

Features

  • Eficient data representation in C++ and interoperability in Python by pybind11.
  • Triple data IO, processing and extraction.
  • Various sampling methods.

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

kgekit-0.24.0.tar.gz (40.7 kB view details)

Uploaded Source

File details

Details for the file kgekit-0.24.0.tar.gz.

File metadata

  • Download URL: kgekit-0.24.0.tar.gz
  • Upload date:
  • Size: 40.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.21.0 setuptools/40.4.3 requests-toolbelt/0.9.1 tqdm/4.30.0 CPython/3.7.3

File hashes

Hashes for kgekit-0.24.0.tar.gz
Algorithm Hash digest
SHA256 90e1dc7c9c53e3cba2390201aab586a4eab7c39716cbdf01df18ada4e73d0237
MD5 b24e783d0b7ad20145c7a9b1a6097212
BLAKE2b-256 b560275882d6445de0638c2d3547bd3481280e244fa9c5f9d92bb9c76f4adf87

See more details on using hashes here.

Supported by

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