Skip to main content

Microsoft Health Futures package containing high level ML components

Project description

Microsoft Health Intelligence Machine Learning Toolbox

Overview

This toolbox aims at providing low-level and high-level building blocks for Machine Learning / AI researchers and practitioners. It helps to simplify and streamline work on deep learning models for healthcare and life sciences, by providing tested components (data loaders, pre-processing), and deep learning models.

Installation

You can install the latest version from pypi via

pip install hi-ml

Documentation

The detailed package documentation, with examples and API reference, is on readthedocs.

Getting started

Examples that illustrate the use of the hi-ml toolbox can be found on readthedocs.

Changelog

We are relying on Github's auto-generated changelog to describe what went into a release. Please check each individual release to see a full changelog.

Links

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

hi-ml-0.3.4.tar.gz (89.6 kB view details)

Uploaded Source

Built Distribution

hi_ml-0.3.4-py3-none-any.whl (107.5 kB view details)

Uploaded Python 3

File details

Details for the file hi-ml-0.3.4.tar.gz.

File metadata

  • Download URL: hi-ml-0.3.4.tar.gz
  • Upload date:
  • Size: 89.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.17

File hashes

Hashes for hi-ml-0.3.4.tar.gz
Algorithm Hash digest
SHA256 b8b0321173ce94b2c8dea14fd760bb15cb42a3e2f250c90b2e615d1831ec7aeb
MD5 db9b65b97887c3862c206e667ddb913d
BLAKE2b-256 252d5592b80b86199ba376bae110609975e72500b3fbd300c57edf30db6caab0

See more details on using hashes here.

File details

Details for the file hi_ml-0.3.4-py3-none-any.whl.

File metadata

  • Download URL: hi_ml-0.3.4-py3-none-any.whl
  • Upload date:
  • Size: 107.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.17

File hashes

Hashes for hi_ml-0.3.4-py3-none-any.whl
Algorithm Hash digest
SHA256 71605fd424da3fe081811fe7cad81f52537b87c0cfc408d2c2f55ca826836625
MD5 5d9c7167a7dc94c15121eea4672259c4
BLAKE2b-256 e5fdb39bd3f6ebbaf4b2e5dcfa21d7bd5204913e7dcf0daf20f29f9a1a62de43

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