Local Hack Day 2017 @ Rutgers University

Problem Statement

People need to identify their skill gaps with the swiftly changing market, and as such, need to understand their current position in the market.

Solution

Our program gives insight into where the user is in the rapidly expanding market space, especially with the growth in technology. By taking in features from your cover letter(in text), such as your experience, degree, and past working history, it predicts a CTC that the general market would have for you.

Next steps

We would like to prgress this idea further by making skills(i.e. Data Science) a factor and giving more precise predictions based on industry(i.e. Finance, IT).

Coded using React.js, Python, Flask, and scikit_learn(for Random Forest Classifier).

Built With

Submitted to

Local Hack Day IV

Created by

I worked on building the Decision Tree/Random Forest ML model, did regex parsing and data preprocessing(value mapping), and built flask restful api for frontend-backend integration.

Krishnan Ram
A high school student trying to use next generation technologies to solve next generation problems.
I worked on connecting with different APIs to get job and college information in order to give salaries with real world data. It was my first time using RegEx so it was a bit tricky, but I did learn a lot on how to accurately mine the data to get the right information. Finally, I worked on mapping the values correctly so the decision tree can rank the user's data better.

Kashyap Murali
I worked on efficiently connecting Front-end with Back-end. Along with creating an full web app with an output of 2 graphs that compare your salary and Years of experience along with an average of others salary and years of experience.

Aditya Patil
I worked on displaying a graph using the data sent to the frontend via the api. I used ReCharts, a graph creating tool that can be easily used with React. I had worked on connecting the frontend to the backend so that I can receive the data that I needed to graph.

Jinal Shah