It is a simple recipe app that comes with data populated with firebase. It is a how-to cook app complete with recipes required to fully cook a specific dish. Its data migration is so simple that with just a few tweaks in its columns/fields you can import any recipe data available on the internet.
Another feature is its ability to list and save the key ingredients needed for a specific dish that you wish to cook in just a single click. This simple and yet handy app is a must-have for all food lovers out there who are in the process of learning how to cook any recipes found on the app.
It’s a simple and straightforward chat application and has the functionality of sending text messages that will be automatically deleted within 24 hours for the initial version.
For the first version app release, we are planning to provide the key features and the main infrastructure of the app. Functionality and Process flow will be its main priority.
For the API we are going to be using Codeigniter and MySQL for the database hosted by Namecheap servers. This will also be using HTTPS protocol for all connection requests and communication to the server.
This is the new design for 2021, first prototyped in Figma and implemented by our volunteers.
This volunteer, with a background in Computer Science, decided to make a web app that can give guidance and direction on what to do if you're not feeling mentally well. One of the methods he implemented in the web application that utilizes React and HTML, there4u, is the guidance for box breathing.
Deploying an open source full stack serverless application to search, sort, and filter the public records on AWS, with CI/ CD (continuous integration, continuous deployment) workflows.Link Project
Developed using Node.js, Express, and Serverless frameworks, and deployed on AWS Lambda. The REST API is developed using AWS API Gateway at this base url (https://q60xzpit4j.execute-api.us-east-1.amazonaws.com/dev). No API Key is required to access the API endpoints at the moment. The backend is also configured to deploy on every repository push on the main branch, using GitHub Actions. Github repository for the back-end source code:
The serverless database is up and running on AWS RDS with PostgreSQL-compatible Aurora engine. The database is publicly accessible with the correct host, username, and password. Only the reader instance is used with the application since the application does not require create, update, delete operations.
This volunteer worked on a lot of projects during his time with the program. He created a number of games such as a snake game, pong, cross road, and many other using Python. I also improved my skills using C language and object oriented programming.
This project focuses on building a game from scratch in C++ without external libraries or game engines. It consists of implementing the game simulation logic, resource management, often hidden functionalities (such as graphics), and integrating on the Windows platform. Currently, it can bring up a Windows graphical application and render primitive shapes, such as rectangles, concerning user inputs (such as mouse clicks). Future work includes supporting more keystrokes, rendering shapes, and interesting game logic.
RND4IMPACT.com 5.0 , the new design for 2023, first prototyped in Figma and implemented by our volunteers.Visit Website
The Project name was "SafeSecretShare". We often need to share sensitive credentials such as account passwords, credit card information, and API credentials with our friends, family, and co-workers. While sharing credentials, we often rely on the security of communication methods such as email and messaging apps such as WhatsApp, Signal, etc. These communication methods are not designed with the safety in mind of sensitive credentials and do not allow security features such as limited-time viewing, automatic deletion, IP address filtering, etc. The project's main idea is to enable users to securely share sensitive credentials.
I have created a back-end repository in Golang containing APIs to store encrypted messages. Github
This Python project implements ideas and problems from the space of quantitative finance. Some simple quantitative problems with theoretical results will be empirically verified using simulation. Some complex problems will also be simulated.
The goal of the project is to simulate ideas from simple problems to more complex problems. Optimization techniques will be implemented to improve the runtime and space complexity.
Machine learning, reinforcement learning, constraint optimization, etc. ideas will be implemented soon. Github