Skip to main content

A platform for managing and serving Machine Learning types.

Project description

Note: HuoguoML is stil under development and can have some unknown issues.

🍲 HuoguoML

When dealing with Machine Learning applications, there is a high management and coordination effort for data scientists, as they have to collaborately analyze, evaluate and update many different models with different metadata on a regular basis. HuoguoML aims to simplify the management process by providing a platform for managing and serving machine learning models. It enables:

  • Individual Data Scientists to track experiments locally on their machine and output models to ML engineers, who then deploy them using HuoguoML's deployment tools.
  • Data Science Teams to set up a HuoguoML tracking server to log and compare the results of multiple data scientists working on the same or a different problem. Then, by setting up a convention for naming their parameters and metrics, they can try different algorithms to solve the same problem and then run the same algorithms again on new data to compare models in the future. In addition, anyone can download and run a different model.
  • ML Engineers to deploy models from different ML libraries in the same way by executing a simple command. Each service is centrally maintained and supports OTA updates. On its own, a HuoguoML Service is based on FastAPI and can be extended with standard FastAPI tools. It supports all use cases, be it storing predictions with middleware or adding new endpoints e.g. for Prometheus.

Installation

HuoguoML can be installed via PyPI. Install the stable version of HuoguoML via PyPI:

pip install huoguoml

or get the development version, which is updated with every commit on the main branch:

pip install huoguoml-dev

Examples

Just starting out? Try out our examples which work out of the box:

Example Description
Tensorflow MNIST Building a MNIST classifier with Tensorflow and HuoguoML

Documentation

Apart from learning from the examples, we highly recommended you go through our documentation, as it gives you a more detailed guide to HuoguoML

Our docs are built on every push to the main or docs branch.

Contributing

We encourage you to contribute to HuoguoML! Please check out the Contributing guide for guidelines about how to proceed.

License

Apache License Version 2.0, see LICENSE

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

huoguoml-dev-1624481463.tar.gz (19.0 kB view details)

Uploaded Source

Built Distribution

huoguoml_dev-1624481463-py3-none-any.whl (2.3 MB view details)

Uploaded Python 3

File details

Details for the file huoguoml-dev-1624481463.tar.gz.

File metadata

  • Download URL: huoguoml-dev-1624481463.tar.gz
  • Upload date:
  • Size: 19.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.5.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.61.1 CPython/3.7.10

File hashes

Hashes for huoguoml-dev-1624481463.tar.gz
Algorithm Hash digest
SHA256 c32d6b91ebcc45c17be5d3cfc567c50de1c5c82850c04d73ad58e5b770db3282
MD5 ca75e5cd3b9f189851ed09035e7e2cf7
BLAKE2b-256 dcc9bda33ec5f82923828c7b33279d986fe51697189b91d68b716cf9b0a6cb0a

See more details on using hashes here.

File details

Details for the file huoguoml_dev-1624481463-py3-none-any.whl.

File metadata

  • Download URL: huoguoml_dev-1624481463-py3-none-any.whl
  • Upload date:
  • Size: 2.3 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.5.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.61.1 CPython/3.7.10

File hashes

Hashes for huoguoml_dev-1624481463-py3-none-any.whl
Algorithm Hash digest
SHA256 70d4a4324424ca288b5b970d0209a7657cb77c5b21c9a24fe0090d7bc32df8bf
MD5 8f19430ed2d45952c10f30d0757b1135
BLAKE2b-256 334e73ba7f807676afdb723bc528348f3a124d7a35a7affc7bc61a7a7e92d535

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