Serve your models with confidence
Project description
Serve models with confidence.
Free software: GNU General Public License v3
Documentation: https://racket.readthedocs.io/en/latest/
Overview
Let’s face it. Building models is already challenging enough. But putting them into production is usually a big enough challenge to grant the employment of an entire separate team. The goal of the project is removing (or at least softening) the dependency on machine learning engineers and devops, enabling data scientist to go from concept to production in minutes.
Features
Easy integration with TensorFlow Serving and Keras
RESTful interface with interactive Swagger documentation
Model introspection: ability to view model performance and input requirements
Ability to deploy automatically different models with a single command
Rich CLI capabilities, going from project scaffolding to training, serving, and dashboarding
Small codebase, statically typed with mypy, and extensive docstrings
Coming Soon TM: Web-ui for managing, introspecting, and deploying models.
Demo
Roadmap
Web dashboard for model management and introspection
Support for Pytorch using ONNX
Path to production: docker-based deployments to major cloud providers
Security capabilities with SSL encryption
Credits
This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.
The icon was created by smashicons.
History
0.1.0 (2018-11-02)
First release on PyPI.
0.2.0 (2018-11-13)
Major feature implementation and documentation
Static typing
Testing - 78% coverage
0.3.0 (2018-11-20)
Major internals refactoring
API unchanged, although external API was made more clear and documented
Project details
Release history Release notifications | RSS feed
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