GP-Kulam

Bingo_tinygame

GP-Kulam.github.io

My portfolio

spec

The score specification file

Pig-game

np_lab

NP_OBA2

FTP

Statastical_Analysis_With_Python_WS

React-Hello-World

link-manager

NLP_Resume_Categorization

AIML_Lab

aiml_termworks

Compiler-Design-Project

it-cert-automation-practice

Google IT Automation with Python Professional Certificate - Practice files

Artificial-Intelligence-and-Machine-Learning-Laboratory-18CSL67

Artificial Intelligence and Machine Learning Laboratory (18CSL67) 6th Semester CSE

ADIS

sd-lab-project-group_2_sd_lab_5th_sem_hackbagpackers

sd-lab-project-group_2_sd_lab_5th_sem_hackbagpackers created by GitHub Classroom

ChatBotScratch

A very introductory and beginner level attempt to make a CHATBOT that responds to certain ruled questions.

Javascript

Assignment from Akrivis-Solutions

HTML_CSS

Assignment from Akrivis-Solutions

IEEE_GIT-Website-Contest-Hackbagpackers

Official website contest for IEEE-GIT

BINGO_Project

The Bingo game using java swings

Prototypes

prototypes of webs and mobile apps

Tic-tac-toe-game

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

slr-py

A simple SLR parser using python