︎
︎

GADFLY AI


/SERVICES
/MISSION
/CONTACT
/BLOG
/PODCAST









Welcome to GADFLY.AI. We weave the real-life narratives of a modern developer's experiences building code for community impact. Teaching creatives and engineers how to explore the world around them through data.




 ︎︎︎scroll to view machine learning stories︎︎︎

/WOMEN IN THE WORKPLACE/BEAUTY TECHNOLOGY/PSYCHOLOGICAL EFFECTS OF SOCIAL MEDIA/TREND ANAYLSIS/ALGORITHMIC FUNDING







/WOMEN IN THE WORKPLACE/BEAUTY TECHNOLOGY/PSYCHOLOGICAL
EFFECTS OF SOCIAL MEDIA/TREND ANAYLSIS/ALGORITHMIC FUNDING



GADFLY.AI_TEAM


Sara Kimmich - Founder, Technical Community Lead
Anova Hou - Creative Director
Kseniia Borovkova -  Digital Community Outreach
Anjali Ramesh - Machine Learning Advocate
Emily Yang - Machine Learning Advocate

Uyen Nguyen - Machine Learning Advocate
Yan Lawrence - Machine Learning Advocate

Anjeli Ramesh


Project_Research On Women

VIEW CODE



“This project is aiming to explore and analyze the experiences of women in the workforce, whether that be during interviews, in the workplace, participation, wage gaps, leave policies, or other factors.”



  1. My favorite failure this week was having very little time to spend combing through the datasets that I had chosen, and instead spending that time taking many many midterms. Although on the bright side, looking at datasets was a nice break in stressing over all the papers waiting to be written.
  2. My favorite false start this week was eliminating the datasets I had previously chosen for different reasons, which led to me either getting rid of them completely, or saving them for later projects that I’m also excited about.
  3. My secret superpower this week was narrowing the scope of my project and getting a clearer idea of what purpose this data science project will serve. This has helped me visualize what I have to do from this point in general terms, which is really reassuring going forward. Having a chosen dataset and a more specific objective makes me feel like a lot of progress has been made from when I first started, and this is comforting, especially with the craziness of this week.
  4.  This was my favorite data visualization this week, because I think it’s a really interesting and unique way to show change. It represents the shift in margin (either more Democratic or more Republican) from the 2016 general election to the 2020 general election in counties across the country. This visualization provides information about a very large number of locations and does it in a way that’s easy to understand and quite simple. I like this concept of representing change, and it relates pretty directly to something I want to show, which is the change in female participation in the workforce in each state from 2011 to 2018.

Uyen
Nguyen



PROJECT_Data Science

VIEW CODE


We are building a prediction algorithm for the Kiva loan project to identify the most needy communities and regions to give financial funding to. Individual funders and the Kiva fund planning team can look at the analysis, which inspects MPI index, historic amount of funding and correlation to economic development, and decide where to continue funding.
  1. What was a favorite failure: logarithmic data transformation for a histogram
  2. What was your favorite false start: not separating my projects into smaller tasks to give myself more motivation to complete each step.
  3. What was your secret superpower: Googling the right thing
  4. What was your favorite data visualization, and why? Treemap, because it shows relational proportions of different categories in a logical way//
  1. What was a favorite failure: finding the right algorithm for my prediction problem
  2. What was your favorite false start: making the problem too complicated.
  3. What was your secret superpower: not afraid to ask questions
  4. What was your favorite data visualization, and why? bar charts, because they are simple to build but can deliver the message across very well.