WiDS Datathon 2024 Challenge
Kaggle Competition (work in progress)
The datathon addresses healthcare inequality. Dataset from Gilead Sciences includes demographic, diagnosis and treatment information for patients diagnosed with breast cancer.
Data exploration ongoing
Portfolio Presentation for iSchool
Milestone requirement
As part of my Master's degree in Applied data science, a practitioner's degree with a strong emphasis on the applications of data science to enterprise operations and processes, I had to present my learnings to my school and faculty associated with the program.
IST782-Presentation-AppliedLearnings-MohitVellanki.pptxVisual Analysis of Syracuse Data
November 2023
As a submission for the hackathon in the first-ever Syracuse Open Data Day 2023, I created a PowerBI dashboard that analyzed different requests submitted through the SyrCityLine app.
Tools used : PowerBI
Hosted on the City Of Syracuse data portal. Click the City's flag below to view the dashboard
NLP Techniques for Text Summarization
October - December 2023
Explored abstractive and extractive text summarization techniques and implemented them on publicly available data to demonstrate the results
Tools used : Python
Motor Vehicle Crash Analysis In Syracuse
October - December 2023
Aimed to understand the reasons for the crashes based on the data available – which includes crash information, and weather conditions at the time of crash. To achieve this and save lives, the data was used to create predictive models that generated insights through a set of research questions.
Tools used : Python, Spark
Analyzing ACS To Identify Zip Codes Prone To Poverty
March - May 2023
An academic project where me and my team used data from the American Community Survey to address poverty-related issues and recommend a data-driven solution for local authorities.
Tools used : Python, R
Hosted on GitHub. Click the GitHub logo below to view the source code.
Providing Actionable Insights To A Health Management Organization
October - December 2022
Provided actionable insights to a Health Management Organization (HMO) by utilizing data analysis techniques and building predictive models to identify expensive customers, ultimately enabling the organization to make informed business decisions
Tools used: R, Shiny
Hosted on GitHub. Click the GitHub logo below to view the source code.
Exploratory analysis showing link between age, BMI and cost of a customer for the organization