As part of my Data Science Fellowship at the U.S. Bureau of Labor Statistics, I developed a tool that automated days of analysis and visualization to quickly extract important highlights and trends from new or revised data. The tool is hosted on BLS' server and isn't available to the public.
(These GIFs were taken with authorization from superiors)
The 1st feature I developed was the Revisions Feature
The 2nd feature I developed was the Outliers Feature
In this project, I applied Machine Learning models to my Goodreads Data to identify my next favorite books 📚among a list of more than 10 000. The project's code can be found here 👨💻
Delphes is an Open-Source Deep-Learning website trained on more than 150 000 tweets from Members of the European Parliament (MEP) that matches European citizens with their closest European Political Group and MEP, based on a simple text-input or Twitter username.
Check out my Presentation of Delphes at Le Wagon's Demo Day
(The video is already set on my presentation to save you time)
In this project, I mapped the 2017 French Presidential Election Results. This resulted in 5 maps (as seen below), one displaying the general results, and four displaying the results of the most popular candidates (François Fillon, Marine Le Pen, Jean-Luc Mélenchon and Emmanuel Macron).
1st Round Presidential Election Results
1st Round Presidential Election Results - François Fillon
1st Round Presidential Election Results - Marine Le Pen
TwittLists analyzes millions of public user-generated Twitter lists to create a ranking of the best Twitter accounts on a given topic ranging from Chess to French Mayors.
In November alone the account reached 500K people!
