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ml-training-api

A Twilio Labs Project

This is a simple python service template for training machine learning models asynchronously.

Falcon + Celery

Example of how to handle training machine learning models asynchronously with Falcon, Celery, and message queues diagram

Quick Start

Spin up the containers:

$ docker-compose up -d --build

Open your browser to http://localhost:8000/ping to view the app or to http://localhost:5555 to view the Flower dashboard.

Trigger a new task with hyperparameters (optional):

$ curl -X POST http://localhost:8000/create \
    -d '{"alpha":0.5}' \
    -H "Content-Type: application/json"

Check the status:

$ curl http://localhost:8000/status/<TASK_ID>

The model used in this repo is a general text classficiation model built using td-idf features and naive bayes model. But you can plug in any model of your own choice.

Let's work together

Everything in this toolkit is released under Twilio Labs and fully open-source. If you find any problems with this, please file an issue or even create a pull request to work together with us on the toolkit. We would love to hear your ideas and feedback!

License

MIT