tarunsinghal92 Goto Github PK

followers: 16.0 following: 6.0 repos: 309.0 gists: 4.0

Name: Tarun K. Singhal

Type: User

Company: U Of T

Bio: I'm an ambitious techie who finds pleasure in all aspects of the cloud-based product. Being an engineer, I found pleasure solving real-life problems.

Location: Toronto

Tarun K. Singhal's Projects

quietnet

Simple chat program using inaudible sounds and a computer's microphone and speaker.

rabbus

A micro-service bus with built-in messaging patterns, for NodeJS and RabbitMQ

react-app-starter-material-ui

A starter project for writing a react app with material-ui components

react-boilerplate-cra-template

:fire: Setup Create React App with React Boilerplate. Highly scalable & Best DX & Performance Focused & Best practices.

react-chartjs

common react charting components using chart.js

react-digraph

A library for creating directed graph editors

react-graph-vis

A react component to render nice graphs using vis.js

react-joyride

Create walkthroughs and guided tours for your features

react-native-boilerplate

A React Native project template for building solid applications through separation of concerns between the UI, state management and business logic.

react-redux-electron-starter-kit

React, Redux and Electron all packaged into one sleek starter pack. Get started the easy way!

react-select

A Select control built with and for React JS

react-slack-feedback

Unofficial React component for gathering user feedback to send to slack.

react-sortable-tree

Drag-and-drop sortable component for nested data and hierarchies

react-spotify

A Spotify client built with React / Redux 🎤🎺🎸🎷

react-treebeard

React Tree View Component. Data-Driven, Fast, Efficient and Customisable.

resolve

Full stack CQRS, DDD, Event Sourcing framework for Node.js

resume-job-description-matching

The purpose of this project was to defeat the current Application Tracking System used by most of the organization to filter out resumes. In order to achieve this goal I had to come up with a universal score which can help the applicant understand the current status of the match. The following steps were undertaken for this project 1) Job Descriptions were collected from Glass Door Web Site using Selenium as other scrappers failed 2) PDF resume parsing using PDF Miner 3) Creating a vector representation of each Job Description - Used word2Vec to create the vector in 300-dimensional vector space with each document represented as a list of word vectors 4) Given each word its required weights to counter few Job Description specific words to be dealt with - Used TFIDF score to get the word weights. 5) Important skill related words were given higher weights and overall mean of each Job description was obtained using the product for word vector and its TFIDF scores 6) Cosine Similarity was used get the similarities of the Job Description and the Resume 7) Various Natural Language Processing Techniques were identified to suggest on the improvements in the resume that could help increase the match score

tarunsinghal92 Goto Github PK

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