My name is Sita Robinson. I am a Junior Data Science major at Drexel University with a minor in Computer Science.
I am expected to graduate with my Bachelors degree in 2020.
I am a treasurer of the Women in Computing Society (WiCS). Another professional organization I'm a part of is IEEE at Drexel University where I'm currently in the marketing committee. My last job was in a data science co-op (6 month internship) at ELAP Services in Chesterbrook, Pennsylvania. In the summer of 2017, I was a Software Engineering Intern at Comcast in Philadelphia. Some of my hobbies include programming, photography, playing the clarinet, playing Scrabble and traveling around the world. I am originally a Northern Virginia/Metro D.C. native.
Data Science Co-op at ELAP Services
September 24, 2018-March 20, 2019
Software Engineering Intern at Comcast
June 19, 2017-August 25, 2017
Beginner: R, Node.js, ArcGIS (ArcMap, ArcGIS Online), LaTeX, Ruby on Rails, Java, Unix, Tableau, JQuery Mobile, JQuery, Flask
Contact me to view other projects
Using fastai which is a Python library to try to detect malaria.
As a student or a professional we feel the need to know what qualifications are needed for a certain job or profession. For this project I scraped Indeed using Beautiful Soup and then used the NLTK library to find stopwords and bigram collocations to find the most frequent words. Then I combined all of this with Flask which is a framework which allows you to run Python on a website. A user can type in a job keyword and location. The result will show the most frequent two words together that come up in the search. From this you can find what might be useful to learn next to add to your resume.
Built machine learning models using linear regression and random forest to see what the most important factors are in graduate admissions. Performed pre-processing and exploratory data analysis. This project was completed using the R language.
Built machine learning models using linear regression and random forest to predict student performance using the Student Performance in Exams dataset from Kaggle. Performed pre-processing and exploratory data analysis. This project was completed using the R language.
Pre-processing and exploratory data analysis steps. Also used scikit-learn to test and train the Mushroom Classification dataset on Kaggle focusing specifically on whether the models can accurately predict and classify whether a mushroom is poisonous or edible. Used classification algorithms including SVM, Naive Bayes, and Logistic Regression.
Data pre-processing and exploratory data analysis on the "Who eats the food we grow?" dataset from Kaggle.
Experimented with text analysis using Python wordcloud, numpy, matplotlib, and Jupyter Notebooks. Used the text from the Adventures of Sherlock Holmes by Sir Arthur Conan Doyle.
An android social app for Drexel University students to collaborate on their schedules with the goal of making class time more efficient, collaborative, and fun. Made using Firebase and Android Studio.View App Video
A fun website that provides educational information about scientific cycles for children.
A few labs and projects from CS 164 my first CS class at Drexel.
A quick Tic-Tac-Toe game. Make sure to turn on your volume.
Ⓒ Sita Robinson 2017