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-0.3.2.tar.gz (89.6 kB view details)

Uploaded Source

Built Distribution

hi_ml-0.3.2-py3-none-any.whl (107.5 kB view details)

Uploaded Python 3

File details

Details for the file hi-ml-0.3.2.tar.gz.

File metadata

  • Download URL: hi-ml-0.3.2.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-0.3.2.tar.gz
Algorithm Hash digest
SHA256 f2ac5d7cf5a3d673a1ad38cd4e708924e27390284dca12b95f22e443c6e54908
MD5 3155e35866b4dada1f04f10e294fc688
BLAKE2b-256 ce1698ff0843ee8beb80623b4e58eb4c5d6a042162f4b8f89797fca388baae8e

See more details on using hashes here.

File details

Details for the file hi_ml-0.3.2-py3-none-any.whl.

File metadata

  • Download URL: hi_ml-0.3.2-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-0.3.2-py3-none-any.whl
Algorithm Hash digest
SHA256 0212eb2583b5eb05e1128c3d08713620054b8754824cfa517c2ca8a2961c7e15
MD5 84485614dd173dc11e899a9dbeef8f7f
BLAKE2b-256 f8e9d49573cda2c6f41900de1e54fa2a7a8c3ab31c8447a45a7740e82c4576d2

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