NASA Data Analysis
I scraped data from SpaceWeatherLive.com to get the top 50 solar flares recorded so far and compared it with NASA's publicly available data. I performed some basic data analysis methods such as integration of the two datasets, implemented entity resolution and concluded with exploratory analysis.
The analysis is done in R. I used the tidyr & readr library for
data manipulation, the dplyr library for entity resolution and the ggplot2
library for the final analysis.
Sun 4k. (n.d.). Retrieved from AlphaCoders.
Scribr
A web application built to address the need for an efficient method of filling out electronic medical documentation by providing automated scribing services. It uses natural language processing and heuristics designed to translate doctors' words into completed medical data sheets. This text will then be run through an algorithm to identify entries for fields in electronic medical record forms, and populate those fields with the entries.
The problem was split into the traditional server & client framework. Node.js was used on the server side to handle communication with Google Cloud Services, a customized medical data form was provided to format the fields that the algorithm would catch, and React.js facilitated the data exchange between them.
Go to project
Peng, J., & Kapoor, S. (n.d.). Scribr. Retrieved from meridiam.github.io/scribr.