Open Door

github repo:


youtube demo:

youtube video here

The Process

I love working with data, and that was largely the inspiration behind this site. I thought it could be a culimination of where all the data could be analyzed that were relevant to me as a student: housing? food? gyms? I was also navigating the concept of budgeting my entire life as a first-year university student, and thought that if there was some way ML could help me accomplish this task, I should build it!

This was my first project using Django (as the REST API) and it really showed me why the framework is so widely used for Python programmers because it has so many different features for filtering, searching, and modelling. One of the most useful features I found was its ORM which enabled me to interact with a PostgreSQL database with just Python code.

This project is one of my favourites because of the numerous ways it analyzes and interacts with data. Using Nivo as a visualization library, I was able to analyze the impact of one restaurant or housing compared with the other places we had in our database.

Sample analytics
Sample analytics from Open Door

Additionally, using common NLP packages like Vader and NLTK, I was able to summarize the general sentiment from Yelp's reviews and give it a general sentiment label of either positive, neutral, and negative.

I loved building this project because most of the features came while building the website. As I learned more about ML and got involved with data analysis, more ideas and more possible use cases for our website came with it. It honestly showed me a lot of capabilities that data science will have for our future, and makes me want to explore more about the intersectionality of data and software engineering.

For more information about the features of the project view the at my Github repo.