vengeance1464 Goto Github PK

basic-react-redux-basics

basic_inheritance_in_java

bricks-protocol-contracts

Contract MVP for BricksProtocol

calculator

calories-tracker

chatbot

chatbot-api

clsssifier-which-classified-whether-a-borrower-paid-the-loan-in-full-lending-club.com

Lending Club connects people who need money (borrowers) with people who have money (investors). An investor you would want to invest in people who showed a profile of having a high probability of paying back. This is a model that will predict this. This data is from before they even went public.I used the lending data from 2007-2010 and classified and predict whether or not the borrower paid back their loan in full. The csv file is in this repository . Here are what the columns represent: credit.policy: 1 if the customer meets the credit underwriting criteria of LendingClub.com, and 0 otherwise. purpose: The purpose of the loan (takes values "credit_card", "debt_consolidation", "educational", "major_purchase", "small_business", and "all_other"). int.rate: The interest rate of the loan, as a proportion (a rate of 11% would be stored as 0.11). Borrowers judged by LendingClub.com to be more risky are assigned higher interest rates. installment: The monthly installments owed by the borrower if the loan is funded. log.annual.inc: The natural log of the self-reported annual income of the borrower. dti: The debt-to-income ratio of the borrower (amount of debt divided by annual income). fico: The FICO credit score of the borrower. days.with.cr.line: The number of days the borrower has had a credit line. revol.bal: The borrower's revolving balance (amount unpaid at the end of the credit card billing cycle). revol.util: The borrower's revolving line utilization rate (the amount of the credit line used relative to total credit available). inq.last.6mths: The borrower's number of inquiries by creditors in the last 6 months. delinq.2yrs: The number of times the borrower had been 30+ days past due on a payment in the past 2 years. pub.rec: The borrower's number of derogatory public records (bankruptcy filings, tax liens, or judgments).

covid19india-react

Tracking the impact of COVID-19 in India

deno-oak

emtrop-react

firestoregoogleappsscript

A Google Apps Script library for accessing Google Cloud Firestore.

hardhat-template

Template to build smart contract with hardhat + typescript + ethers

ieee_smart_attendance

IEEE smart attendance app

imad-app

Base repository for IMAD course application.

kanban-task-management-backend

kanban-task-management-ui

markdown-editor

myapplication22

next

nft-fractionalizarion-contract

nft-fractionalization-backend

nft-fractionalization-contract

nft-fractionalization-ui

nlp-project-to-classify-yelp-reviews-

Each observation in this dataset is a review of a particular business by a particular user. The "stars" column is the number of stars (1 through 5) assigned by the reviewer to the business. (Higher stars is better.) In other words, it is the rating of the business by the person who wrote the review.The "cool" column is the number of "cool" votes this review received from other Yelp users. The "useful" and "funny" columns are similar to the "cool" column. Source-kaggle.com.The dataset is attached to this repository as .csv file

ordermanager

privacy-policy

reachify

recipefinder

Get Recipes based on ingrediants available in kitchen

springbootforbeginners

Spring Boot Tutorial For Beginners