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Accenture-learning-modules
Accenture pre hiring learning modules - tekstacOnlineQuiz
This is an online quiz / exam website where the admin can add the tests, remove the tests, remove the users, view statistics, view ranking, set the test timer and also check / view feedback. This is developed in HTML5, CSS3, Javascript, PHP. The database is used is MySQL.Dog-Breed-Recognition-Flutter
This is a Flutter Application for Dog Breed Recognition. Tensorflow lite is used for creating the ML modeladarsh-dayanand
face-mask-detection
News-Application-Flutter
Flutter application to fetch news from different sources all at a single applicationnotes-taking-angular-app
Notes taking application in Angular and MyScriptflight-booking
food-app-ui
Food App UI - React Nativeexercise-tracker
flutter-dictionary
This is a dictionary application developed using fluttersystem-generate-sms
Send system generated SMS with local and toll-free numbers, short codes, custom alphanumeric sender IDs, or using your own existing phone numbers.resume-matching-scoring
The main objective of this project is to compare the given resume with application of job description in the company and give suitable result in terms of percentage and to score a resume and visualize it.flutter-hangman
online-store-mern
parse-web-signup
This code is used to sign up an user to the parse server (back4app) through the web browser / web site.task-manager-api-server
This is a task manager application backend where users can register and add/ modify/ delete task. User has the options like login/ signup/ modify/ delete user profile/ show user profile. This project is done using Node JS and Express with JWT and bcryptjshome-automation-android
An android application which logs in users through sending an OTP to their mobile number and register the user. Then the app check for the paired devices and if it's a bulb. the connection will be successful. The bulb can then be controlled using the app.MalariaDetection-machine-learning
This is a simple project to detect the malaria infected people by their blood samples using Machine Learning. Random forest classification is used in this project. The accuracy is around 90%. The data-set used is the real data-set. The data-set is obtained from Kaggle.Love Open Source and this site? Check out how you can help us