<h2 id="live-demo">Live Demo</h2>
<p><a href="http://verbe.cc/" class="autolinkedURL autolinkedURL-url" target="_blank">verbe.cc</a></p>
<h2 id="overview-of-the-three-components">Overview of the three components</h2>
<p><img src="https://cdn.hashnode.com/res/hashnode/image/upload/v1623520345608/rwgCQBu10.png" alt="verbecc_diagram.PNG" /></p>
<p>It knows how to conjugate thousands of verbs and for unknown verbs, it uses a machine-learning algorithm to predict the conjugation template.</p>
<h2 id="part-1-the-python-library-verbecc">Part 1 - The python library - verbecc</h2>
<p><a href="https://pypi.org/project/verbecc/" class="autolinkedURL autolinkedURL-url" target="_blank">pypi.org/project/verbecc</a>
<a href="https://github.com/bretttolbert/verbecc" class="autolinkedURL autolinkedURL-url" target="_blank">github.com/bretttolbert/verbecc</a></p>
<h2 id="part-2-the-dockerized-microservice-verbecc-svc">Part 2 - The Dockerized microservice - verbecc-svc</h2>
<p><a href="https://github.com/bretttolbert/verbecc-svc" class="autolinkedURL autolinkedURL-url" target="_blank">github.com/bretttolbert/verbecc-svc</a></p>
<h2 id="part-3-the-dockerized-web-front-end">Part 3 - The Dockerized web front-end</h2>
<p><a href="https://github.com/bretttolbert/verbecc-web" class="autolinkedURL autolinkedURL-url" target="_blank">github.com/bretttolbert/verbecc-web</a></p>
<h3 id="credits">Credits</h3>
<ul>
<li>Credit to Pierre Sarrazin for the French XML conjugation templates, derived from his project Verbiste (defunct)</li>
<li>Credit to Sekou Diao for the ML template prediction logic, derived from their older project <a target="_blank" href="https://github.com/SekouD/mlconjug">mlconjug</a> however they have a newer version out now <a target="_blank" href="https://github.com/SekouDiaoNlp/mlconjug3/">mlconjug3</a> </li>
</ul>


## Live Demo

http://verbe.cc/

## Overview of the three components

![verbecc_diagram.PNG](https://cdn.hashnode.com/res/hashnode/image/upload/v1623520345608/rwgCQBu10.png)

It knows how to conjugate thousands of verbs and for unknown verbs, it uses a machine-learning algorithm to predict the conjugation template.


## Part 1 - The python library - verbecc

https://pypi.org/project/verbecc/
https://github.com/bretttolbert/verbecc

## Part 2 - The Dockerized microservice - verbecc-svc

https://github.com/bretttolbert/verbecc-svc

## Part 3 - The Dockerized web front-end

https://github.com/bretttolbert/verbecc-web


### Credits

* Credit to Pierre Sarrazin for the French XML conjugation templates, derived from his project Verbiste (defunct)
* Credit to Sekou Diao for the ML template prediction logic, derived from their older project [mlconjug](https://github.com/SekouD/mlconjug) however they have a newer version out now [mlconjug3](https://github.com/SekouDiaoNlp/mlconjug3/) 

Brett Tolbert's Blog

Brett Tolbert's Blog

verbecc - python library, dockerized microservice and web app for verb conjugation in French, Spanish, Italian, Portuguese and Romanian, powered by ML

Live Demo

Overview of the three components

Part 1 - The python library - verbecc

Part 2 - The Dockerized microservice - verbecc-svc

Part 3 - The Dockerized web front-end

Credits