Projects

Nuxt Fund Manager

"Nuxt Fund Manager" is a web application built with Nuxt.js that helps users explore and track investment funds. It uses Tailwind CSS with custom theming for styling.


Here's a breakdown of its core features:

  • Fund Listing: It fetches a comprehensive list of investment funds from an external API, providing users with a centralized resource for discovering available options.


  • Search Functionality: A search feature allows users to quickly and easily find specific funds by name or other relevant criteria.


  • Favorites: Users can save their preferred funds to their browser's local storage, enabling them to build and maintain a personalized list of investment options for future reference.


By leveraging Nuxt.js, this application benefits from features like server-side rendering, automatic code-splitting, and a file-based routing system, resulting in a performant and user-friendly experience. This makes it an efficient and convenient tool for anyone interested in exploring and keeping track of investment funds.




Started on Jan. 14, 2025, 7:41 p.m.
Updated on Jan. 21, 2025, 1:50 p.m.
Status:
Tags: Vue

Project Link : https://github.com/Apfirebolt/Nuxt_fund_manager

Technologies Used : Nuxt 3, Vue, Tailwind CSS, API


Images:
Index
Saved Funds
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Games API App in Next JS

This project is a simple Next.js application that serves as a database for games. It allows users to view game entries from the API https://softgenie.org/api/games. The application is built using Next.js for server-side rendering and optimized performance. It uses Material UI for beautiful styled components following Material design patterns.


The project is deployed here https://next-games-database.vercel.app for the time being.



Started on Dec. 29, 2024, 10:20 p.m.
Updated on Feb. 7, 2025, 10:33 a.m.
Status:
Tags: React

Project Link : https://github.com/Apfirebolt/next_games

Technologies Used : Next JS, Javascript, HTML, CSS, Tailwind CSS


Images:
Homepage
Detail
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Amiibo Database an using Nuxt

This is a hobby project created in Nuxt JS to test the features of Nuxt and getting hands-on experience with the framework. The project utilises the Amiibo API to fetch data about various Amiibo figures.

This is some back-end changes

At the time of writing this post the project is deployed here :-

https://github.com/Apfirebolt/amiibo_api_database_in_nuxt



Started on Dec. 29, 2024, 10:18 p.m.
Updated on Jan. 10, 2025, 8:45 a.m.
Status:
Tags: Vue

Project Link : https://github.com/Apfirebolt/amiibo_api_database_in_nuxt

Technologies Used : Nuxt, Javascript, Headless UI, Pinia


Images:
Homepage
About
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Titanic Survival Prediction using Scikit with PyQT5 GUI

As a Software Engineer, I've mostly dealt with Web Applications. But recently, I felt the pull of uncharted territory: machine learning. Intrigued by the possibilities, I decided to embark on a project that combined my existing skills with this exciting new field. This minor hobby project aimed to predict the survival of passengers aboard the Titanic.


Why this topic?


The Titanic dataset is one of the most popular datasets available on Kaggle. It is often the first project of many ML enthusiasts try their hands on similar to "Hello World". The dataset is clean and clear with minimal modifications required in terms of missing values.


Why PyQt5?


I chose PyQt5 to create a user-friendly interface for my project. PyQt5 allowed me to build a graphical interface where users could input passenger details and receive a survival prediction. This not only enhanced the user experience but also provided a visual representation of the model's output.

Learnings from this project


I learned the basics of data cleaning, feature engineering, feature selection, model training and much more from my first elementary ML project

Completing this project gave me a sense of accomplishment and a newfound appreciation for the power of machine learning. It allowed me to merge my desktop app development skills with ML to create innovative applications.



Started on Jan. 24, 2025, 3:56 a.m.
Updated on Jan. 24, 2025, 4:01 a.m.
Status:
Tags: Python

Project Link : https://github.com/Apfirebolt/titanic_survival_prediction

Technologies Used : Pythion, Scikit-Learn, pyQt5


Images:
Gui1
Prediction result
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Media Player in Python using PyQT5

To enhance my desktop application development skills, I developed a Media Player using Python and PyQT5.


The Media Player has basic controls like a slider to move to any point in the video. There is a volume controller, you can also see file information related to a video. PyQT5 was used because it is rich in classes which are very useful for controlling multi-media contents like audio and video files.



Started on Jan. 24, 2025, 11:42 a.m.
Updated on Jan. 24, 2025, 11:54 a.m.
Status:
Tags: Python

Project Link : https://github.com/Apfirebolt/media_player_in_pyqt5

Technologies Used : Python, PyQt5


Images:
GUI-1
File Info
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