Skip to main content

Machine Learning Wrappers SDK for Python

Project description

Machine Learning Wrappers SDK for Python

This package has been tested with Python 3.9, 3.10 and 3.11

The Machine Learning Wrappers SDK provides a unified wrapper for various ML frameworks - to have one uniform scikit-learn format predict and predict_proba functions.

Highlights of the package include:

  • A dataset wrapper to handle scipy sparse, pandas and numpy datasets in a uniform manner.
  • A model wrapper to handle models from various frameworks uniformly, including scikit-learn, tensorflow, pytorch, lightgbm and xgboost

Please see the github website for the documentation and sample notebooks: https://github.com/microsoft/ml-wrappers

Project details


Download files

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

Source Distribution

ml_wrappers-0.6.3.tar.gz (41.9 kB view details)

Uploaded Source

Built Distribution

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

ml_wrappers-0.6.3-py3-none-any.whl (53.8 kB view details)

Uploaded Python 3

File details

Details for the file ml_wrappers-0.6.3.tar.gz.

File metadata

  • Download URL: ml_wrappers-0.6.3.tar.gz
  • Upload date:
  • Size: 41.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for ml_wrappers-0.6.3.tar.gz
Algorithm Hash digest
SHA256 4d20f01356255a52a065c47691ee7bf87df982176a78e61e14b775fe7d527e46
MD5 dc07cd032762e575d6c6ca9fb936453d
BLAKE2b-256 538a5d3db50301011ac1650cbd76cbfbfdd8203599755104a7fff7a50d6a8bec

See more details on using hashes here.

File details

Details for the file ml_wrappers-0.6.3-py3-none-any.whl.

File metadata

  • Download URL: ml_wrappers-0.6.3-py3-none-any.whl
  • Upload date:
  • Size: 53.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for ml_wrappers-0.6.3-py3-none-any.whl
Algorithm Hash digest
SHA256 8d9fbd1d415cd7a82191f7ca5b4d31fdf7163118cde3e97881ea19f12e7259aa
MD5 33bf9b3d9824a90421d2830c236fc219
BLAKE2b-256 8ef48717f8dad7fbbcd3a80c2f457118849a079cff26e8f30b9b367f157e5019

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