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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
A changelog is maintained on Github
Links
- Github https://github.com/microsoft/hi-ml
- Project InnerEye http://aka.ms/InnerEye
1 maintainer
Metadata
1 maintainer
Release files for hi-ml 0.1.0.post598
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| hi-ml-0.1.0.post598.tar.gz | 4.1 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| hi_ml-0.1.0.post598-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 9.4 kB
Release files / hi-ml-0.1.0.post598.tar.gz
| Download URL | hi-ml-0.1.0.post598.tar.gz |
|---|---|
| Size | 4.1 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Release files / hi_ml-0.1.0.post598-py3-none-any.whl
| Download URL | hi_ml-0.1.0.post598-py3-none-any.whl |
|---|---|
| Size | 5.3 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
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