Project Description In this project, I predict the Indoor Location of users using Wifi fingerprints with a combination of Principal Component Analysis (PCA) and Multi-label Classification using skmultilearn. Many businesses and service providers rely on localization services in order to better serve their patrons. Thanks to the inclusion of GPS sensors in mobile devices, outdoor […]
Disaster Response Message Classification Pipelines (NLTK & Flask)
Project Description Figure Eight Data Set: Disaster Response Messages provides thousands of messages that have been sorted into 36 categories. These messages are sorted into specific categories such as Water, Hospitals, Aid-Related, that are specifically aimed at helping emergency personnel in their aid efforts. The main goal of this project is to build an app […]
Ciara McGuire, Data Scientist and kdb+ Developer at First Derivatives
I recently spoke to Ciara McGuire at First Derivatives about her role as a data scientist and kdb+ developer. She is an incredibly focused woman, who fears no challenge and is a picture of class. Learn more about this very talented woman and her company here. Tell us a little about yourself? I’m Ciara […]
Analyzing Kickstarter Campaigns with Interactive Visualizations
Kickstarter is an enormous crowdfunding website that supports thousands of people in actualizing their dreams. I was curious about how different categories perform and what insight can I provide to someone who wants to start a project on kickstarter. I used Kickstarter data since 2009, and created interactive visualizations using the Python Library Plotly. Feel […]
A Closer look at the Historic Number of Women in Elective Office 2019
January 3rd, 2019 , was an historic day for women. The 116th congress inaugurated a record number of women and especially women of color making it the most diverse class of lawmakers in history. Read more here. Given the grandeur of this event and in honor of these women, I created an infographic that demonstrates […]
Identifying Customer Segments for Mail-Order Sales Company with PCA and KMeans Clustering
In this project, I explore Data from a Mail-Order Sales Company and use unsupervised machine learning techniques to help them identify segments of the population for direct marketing campaigns that would have the highest rate of return. You can find the full code here and below. Here’s a quick overview of the data and analysis that took place. […]
What Flower is this? Developing an Image Classifier with Deep Learning using Pytorch
In this project, I develop a deep learning model and train it on a large set of flower image data in order to accurately predict the names of flowers in completely new images. You can find the full code here and below. I had quite a bit of fun analyzing this beautiful British flowers data […]
Ivana Veliskova, Front-End Engineer at Guru Technologies
I recently spoke to Ivana Veliskova, a Front-End Engineer at Guru Technologies. Ivana is such a vibrant young woman, a dancer turned engineer, an active member of the Girl Develop It community and a woman with an intense bias to action. Read her story here. Tell us a little about yourself and about how you […]
Megan Robertson, Data Scientist at Nike
I sat with Megan Robertson, Data Scientist at Nike to speak about her journey. Megan is an incredibly dedicated and smart young woman. With eloquence, she can alternate between speaking about history and current affairs, to discussing theoretical mathematics and statistics, to being a leader on the basketball court. Read more about Megan and hear […]
Code4PA: Deep Learning Neural Networks to address the Opioid Epidemic
Code4PA is a codeathon that encourages learning, collaboration, growth, innovation, and fun among PA’s network of technical talent. Through a series of collaborative events, teams will utilize state and local data to generate ideas, designs, prototypes and/or apps to increase transparency and efficiency for public engagement with the government. This year’s theme is to help Pennsylvania […]