Web Development
Projects focused on creating responsive, functional websites using technologies like HTML, CSS, JavaScript, Django, and WordPress. These projects enhance user experience and ensure seamless interactions across devices.
Overview
Neurospy is a machine learning project that uses neural signal data collected from Kaggle datasets to analyze brain activity and predict neural patterns. The project leverages Python and deep learning models to process and interpret complex neural data, providing insights into neuroscience and related fields.
Key Features
Data Collection: Utilizes publicly available neural datasets from Kaggle
Deep Learning Models: Trained using Python with advanced models, such as Convolutional Neural Networks (CNN)
Real-Time Predictions: Predicts brain activity and neural patterns based on processed data
Visual Insights: Visualizes neural patterns and predictions for research and analysis
Neural Network Integration: Custom-designed neural networks to improve model accuracy and performance
Process
Data Collection: Data was collected from Kaggle, focusing on neural signal datasets.
Preprocessing: Cleaned and formatted the data for training, ensuring quality inputs for models.
Model Training: Trained deep learning models using Python, focusing on CNNs for neural signal analysis.
Testing: Evaluated model accuracy and refined the models for optimal predictions.
Visualization: Developed visual representations of predictions for easier understanding and research purposes.
Deployment: Implemented the model for real-time analysis, making predictions based on new neural data.
This structure highlights how Kaggle data, Python, and deep learning were used to build the Neurospy project, providing a clear process and key features.
My Portfolio
Overview
This portfolio project serves as a comprehensive showcase of my professional journey, skills, and projects. Built with Python, Django, Bootstrap, and Docker, the website is designed to provide visitors with an interactive and user-friendly experience. It also incorporates Django’s built-in administration panel for efficient content management.
Key Features
Dynamic Content Management: Utilized Django's admin panel for seamless updates to portfolio content.
Modern Design: Responsive and elegant interface developed with Bootstrap.
Scalability: Dockerized environment for consistent deployment and scalability.
Project Details: Individual pages highlight projects like ECO Watch, Neurospy, and Seat Reservation.
Contact Functionality: Includes a contact section to facilitate communication.
Media Integration: Handles and displays static and media files dynamically.
Process
Project Setup: Created a Django application structure and configured the environment using Docker.
Frontend Development: Designed responsive templates using Bootstrap and integrated dynamic content.
Backend Development: Implemented Django for content management and routing, leveraging its built-in admin panel for control.
Database Integration: Configured SQLite for data storage, including project descriptions, contact information, and media.
Deployment: Utilized Docker to containerize the application and ensure platform consistency.
Testing: Conducted cross-browser and device compatibility tests to ensure a seamless user experience.
Project Directory Highlights
MyPortfoliocontains core application settings and configurations.templatesincludes HTML templates for various pages likeindex.htmland project-specific details.docker-compose.ymlandDockerfiledefine the Dockerized environment.db.sqlite3stores all project data securely.
UAV Renting
Overview
The UAV Rental Web Application is a user-friendly platform designed to facilitate the renting of Unmanned Aerial Vehicles (UAVs). Built using Python, Django, and Bootstrap, the application provides a seamless experience for both renters and administrators. The platform also uses Docker for deployment, ensuring a reliable and scalable environment.
Key Features
User Authentication: Secure login and registration features for renters and admins.
UAV Management: Add, update, and delete UAVs with an intuitive interface.
Rental Booking System: Users can browse available UAVs, book rentals, and manage reservations.
Admin Functionality: Leveraging Django’s admin panel for managing users, UAVs, and rentals.
Dynamic Content: Responsive design with Bootstrap for optimal user experience across devices.
Additional Pages: Informative pages like About, Services, and Contact to enrich user interaction.
Process
Project Initialization: Created the Django project structure and configured environment settings using Docker.
Database Design: Implemented SQLite to manage UAV, rental, and user data.
Frontend Development: Designed templates for various functionalities, including booking, listing, and account management, using Bootstrap for responsiveness.
Backend Logic: Built core functionalities such as UAV listing, rental processes, and user authentication with Django.
Deployment: Containerized the application using Docker for easy deployment and scalability.
Testing and Optimization: Conducted rigorous testing to ensure smooth navigation and efficient processes.
Notable Templates
index.html: Home page showcasing the platform's features and UAV listings.list_uavs.html: Displays all available UAVs with detailed information.rent_uav.html: Allows users to initiate rental bookings.list_leases.html: View and manage rental agreements.contact.html: Enables users to reach out for inquiries or support.
Technologies Used
Backend: Python, Django
Frontend: HTML, Bootstrap
Deployment: Docker
Database: SQLite
This project reflects my expertise in web development, showcasing my ability to create robust and scalable applications tailored to specific user needs. The UAV Rental Web App stands as a testament to my commitment to delivering functional and visually appealing solutions.
EtherURL
Overview
EtherURL is a web application designed to make Ethereum contract interactions more accessible through QR codes and trusted certificates.
Features
Designed using Figma and currently being developed with Python, Django, and AWS.
Includes light mode and multi-language support for enhanced usability.
Status
This project is ongoing, and further details will be shared upon completion.
