From Meta, a Wikimedia project coordination wiki

Sheilakaruku (she/her) Outreachy/Round 25(Intern at Wikimedia Foundation).

I'm a software developer from Nairobi, Kenya.

I attended ALX software engineering program/bootcamp from February 14th to December 5th 2022. I learnt some foundational concepts in Python, HTML, CSS, Git and Javascript. Im still building up on more skills progressively as I journey on my programming journey.

As I encounter new projects, it gives me an opportunity to learn new concepts and adding onto more knowledge.


My internship runs from December 2022 until March 2023. It was sponsored by Outreachy, a project of the Software Freedom Conservancy.

I however worked on a different project during the contribution project Develop a web app for editing Toolhub records, but eventually ended up being selected to do a totally different project Develop a web app for patrolling based on the new ML based service to predict reverts.

Project description

The Research team is working on improving the Machine Learning based tools to support Wikimedia Patrollers. As part of this effort we are developing a new model to detect revisions that require the patroller's attention.

The current model is based on implicit users’ feedback (revisions that have been reverted), and gives recommendations on which revisions are likely to be reverted. To improve this model and to make it easier to use its output, we want to build a web app that allows users to 1) rate the quality of the recommendation and 2) directly revert edits based on these recommendations.

The web app allows users to give explicit feedback on our recommendations as well as allow them to directly revert revisions when needed. The app should be able to connect with the API to pull the recommendations and show them to the users. Also it should save the users feedback allowing to retrain/finetune our existing model.


Diego Saez Muniza A