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Tal

A machine learning powered tool to help recruiters.

Group Members + Contributions

Nikhil Bose: Developed and contributed to the UI + Design, the recommender, JS to transfer information and backend/database, video

Ribhu Lahiri: Developed the ML algorithm for the candidate recommender, built the REST API and designed the data schema of the database

Alvin Vanegas: Developed the UI and primarily wrote HTML and Javascript code to link the web pages together

Source Code Files

  • index.html: landing page of our webpage, contains front end code of our login page.
  • index.js: javascript code for our login page, handles user input for entering out web page and sends it to the database.
  • profile.html: front-end code for the user's profile which contains past models they have created
  • profile.js: javascript code for the user's profile, sends the model's name to database.
  • input.hmtl: front-end code for the input page, contains the necessary inputs to create the model.
  • input.js: javascript code that handles the user's inputs and sends it to the database and to the script to run the recommendor.
  • output.html: front-end code to display the data visualizations and the results of the recommendor base on the users input.
  • output.js: contains the javascript code to pull the necessary data from the database to create the data visualizations and to output the results of the model.
  • model (in server/model/): contains the data schema for the required data models for student, recruiters and groups.
  • controllers (in server/controller/: contains the queries to serve data from the database through a REST API
  • perceptron: a simple 2-layer perceptron, with an input layer of 10 units. Trained on given company data for binary classification of potential hires
  • test_data.csv - test data file
  • train_data.csv - train data file

Demo Video

https://youtu.be/S3X9qhw-OTY

About

Tal is an ML-powered utility for recruiters and hiring managers

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