chiragsoni95 Goto Github PK

autograder

:trophy: Automatically grade english essays using NLP techniques (This is not a ML model).

chiragsoni95.github.io

A website to display my work, interests and my web development skills. My Link: https://ChiragSoni95.github.io

codinginterviews

This repository contains coding interviews that I have encountered in company interviews

data-driven_building_simulation_projects

deep_learning

added all materials

extremecluster_parallelprocessing

Parallel Programming lab assignments and projects using High Performing Clusters called Extreme provided by UIC ACCC powered by Acer Labs.

fuzzyjess

Loan Application Expert system is a rule based expert system designed using FUZZY JESS wherein information of a loan applicant is asserted by the user of the Bank, and finally concludes whether applicant is eligible to apply for a loan or not. System also provides suggestions to the user of the system to help him/her to make a decision in a very convenient manner. The expert system checks for all the boolean and Fuzzy parameters asserted by the user and finally claims the decision depending upon its interpretation and a few important rules set in the bank’s policy.

geeksforgeeks-python

GeeksforGeeks Algorithms and Questions implemented in Python

iml-mini-project-5

You are working for a non-profit that is recruiting student volunteers to help with Alzheimer’s patients. You have been tasked with predicting how suitable a person is for this task by predicting how empathetic he or she is. Using the Young People Survey dataset (https://www.kaggle.com/miroslavsabo/young-people-survey/), predict a person’s “empathy” on a scale from 1 to 5. You can use any of the other attributes in the dataset to make this prediction.

kitti-road-semantic-segmentation

Implementation of semantic segmentation of FCN structure using kitti road dataset. I used a tensorflow and implemented a segmentation algorithm with a mean-iou score of 0.944.

loan-application-expert-system-in-jess

Loan Application Expert system is a rule based expert system designed using JESS wherein information of a loan applicant is asserted by the user of the Bank, and finally concludes whether applicant is eligible to apply for a loan or not. System also provides suggestions to the user of the system to help him/her to make a decision in a very convenient manner. The expert system checks for all the parameters asserted by the user and finally claims the decision depending upon its interpretation and a few important rules set in the bank’s policy.

models

Models and examples built with TensorFlow

msapriori

MSApriori algorithm is capable of classifying rare classes. The performance evaluation of the proposed algorithm has been done for different data sets and in comparison with existing technique like Apriori algorithm it is found that algorithm has efficient and superior performance for classifying rare cases.

netica-j_applied_ai

Bayesian Network designed using NETICA wherein information of different type of loan applicants and types of loan is asserted by the user of the Bank, and finally concludes whether applicant will be to repay loan or not.

netica_bayesian_influence

Loan Repayment Decision system is a combination of Bayesian Network and influence Diagram designed using NETICA wherein information of different type of loan applicants and types of loan is asserted by the user of the Bank, and finally concludes whether applicant will be to repay loan or not.Accurately predicting whether a loan will be repaid (credit" scoring) is an important task for any bank.Furthermore, the decision regarding the deadline if it needs to be extended or not is made using the utility and decision node in influence diagram. High accuracy benefits both the banks and the loan applicants.

neuralnetwork_keras

First neural network model using the powerful Keras Python library for deep learning.

node-js

Examples, Assignments and Application developed during the course NodeJS, Express and MongoDB

nouveau_scrum

Project management scrum tool for developers and managers following agile programming methodology

offlinevoting-android-application

Offline Voting Application

onlinelearning_application

Android Online Learning Application

random-java-program-generator

Graduate course project which provides experience in creating a generator that creates a syntactically correct but semantically meaningless Java Program

react

React application developed during the course Front-end development with ReactJS

rest_api

Building professional REST APIs with Python, Flask, Flask-RESTful, and Flask-SQLAlchemy

rssnewsfeed-android-application

RSSNewsFeed Android Application

signs-digit-classification

Deep learning neural network model to recognize numbers from 0 to 5 in sign language with a pretty impressive accuracy of 95% on training data and 72% on the test data

smarket-smartmarket

:trophy: System for recognizing and tracking patterns within data so as to not only react but also anticipate the customer needs in advance.

staticcodeanalyzer

Determine the common bugs after analyzing pattern of patches for various issue/bug reports

stockevaluator

Monte Carlo simulator on a Octa Pi cluster using Spark and Kubernetes

stores_rest_api

A REST API to access items, stores, user authentication.

twitter_sentiment_analysis

Given a collection of tweets, classify them into four classes namely: positive, negative, neutral and mixed. The tweets used here are pertaining to two US presidential candidates namely: Barack Obama and Mitt Romney. By classifying the tweets into the mentioned classes we would be capable of predicting the opinion of the public and get a sense of the outcome of the election.