(^not always in that order)
Hi! I am Debshila. I am a researcher at OpenStax, an educational non-profit affiliated with Rice University, Houston, TX, USA. My role here involves working with multimodal educational data from institutions all over the United States. Most of my work is done using the R suit of tools. But I have also done some work with Python. Give my work profile, I often like to think of myself as Data Jan-Itor.
Check out some of the data analysis and machine learning projects that I have been working on outside my work.
Besides wrangling data, I am on the Rice University ballroom dance team, and a serial dog petter.
If you are a foodie in Houston, TX, then you look forward to this time of the year for the Houston Restaurant Weeks (HRW). A number of local restaurants come together to offer special menus and donate a part of each customer served to the Houston Food Bank. While this is a wonderful initiative, the information displayed on their website makes it difficult to search through. The overarching goal of this project is to aid HRW enthusiasts while they decide on which restaurants they want to visit this year.
Checkout the app: Explore Houston Restaurant Weeks, 2019
Code: HRW Github Repo
People rarely read privacy policy documents. However, with the recent privacy breaches and GDPR coming into effect, individuals are recognizing the need to examine privacy policies that they previously blindly trusted. To facilitate examination of privacy policies, this web app basically generates summaries for privacy policy documents by selecting the most important sentences from these documents. The app leverages the textrank algorithm as implemented by the gensim package (https://radimrehurek.com/gensim/summarization/summariser.html).
In addition, the app displays the results of an Latent Dirichlet Allocation (LDA) based topic model (https://radimrehurek.com/gensim/models/ldamodel.html) trained on > 1000 privacy policy documents (https://usableprivacy.org/data), visualized using the pyLDAvis LDA visualizer (https://pyldavis.readthedocs.io/en/latest/readme.html#usage). This interactive illustration basically displays the underlying themes in privacy policy documents grouped into topics, the relationship amongst these topics (spatial proximity of the topics), and the top keywords from the topics.
Checkout the app: Gist do it!