plthiyagu Goto Github PK

repo-2018

Deep Learning Summer School + Tensorflow + OpenCV cascade training + YOLO + COCO + CycleGAN + AWS EC2 Setup + AWS IoT Project + AWS SageMaker + AWS API Gateway + Raspberry Pi3 Ubuntu Core

repo-2019

Google Assistant API + Raspberry Pi, Infrared, Google Cloud Platform Natural Language, AWS Forecast, Anomaly detection, Mind Controlled Apparatus

repo01

My First Repository

restapi-postman

ML Model need to be deployed so that client can easily access them through API Call. Flask Framework helps this process with less dependency.

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

resume-parser

Analyze, score and rank a collection of PDF resumes using machine learning

resume_filtering

A resume filtering based on natural language processing

resumefilteringtask

Resume Filtering Task Using Machine Learning Approaches

resumeparser

A framework to parse resumes, extract contact & other information, and check for required terms

resumes-filtering

Thakaa center challenge: search in the data sets for resumes and job descriptions to find the best suitable matches.

scala

All Algorithms implemented in Scala

scalacaster

Purely Functional Algorithms and Data Structures in Scala

scalgos

algorithms in scala

scikit-learn-beginners-tutorials

Abridged implementation of the official scikit-learn beginner tutorials

scikit-learn-tips

:robot::zap: Daily scikit-learn tips

scipy-2016-sklearn

Scikit-learn tutorial at SciPy2016

segan_pytorch

Speech Enhancement Generative Adversarial Network in PyTorch

seldon-core

An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models

sentiment-analysis-of-amazon-review-data

Used Kaggle's Amazon review data to predict the sentiments that the reviews express. Used scikit for data pre-processing and implemented machine learning techniques to classify data.

sentiment-analysis-on-amazon-reviews-using-python

serverless-application-model

AWS Serverless Application Model (SAM) is an open-source framework for building serverless applications

serving

A flexible, high-performance serving system for machine learning models

sharing_isl_python

An Introduction to Statistical Learning with Applications in PYTHON

sheetfu

Python library to interact with Google Sheets V4 API

shell-scripting-tutorial

A complete begineers guide to learn shell scripting from scratch which includes Videos, Practice scenarios and project idea.

simple_tensorflow_serving

Generic and easy-to-use serving service for machine learning models

simplystats

Simply Statistics

sippycup

SippyCup is a simple semantic parser, written in Python, created purely for didactic purposes.

skeleton-notebook

A skeleton notebook template for supervised machine learning and data science projects.

sklearn_tutorial

Materials for my scikit-learn tutorial