Safia Faiz@safia_faiz930

This project is an AI-powered content generation platform designed to streamline business marketing. By leveraging advanced LLM models like Gemini and Qwen, the system allows users to input a company description or marketing prompt. It automatically generates SEO-optimized blog posts and high-quality promotional images. The backend is built with FastAPI and integrates seamlessly with a frontend hosted on Vercel. Each type of content is easily downloadable, making it ideal for marketers, startups, and agencies aiming to scale content creation efficiently. The platform bridges the gap between AI capabilities and real-world marketing needs, saving time and maximizing brand impact.

Ensuring optimal network performance and efficient bandwidth allocation in modern digital infrastructures is crucial, especially in educational institutions where multiple nodes compete for resources. This project introduces a Smart Network Resource Allocation System that leverages Software-Defined Networking (SDN), machine learning, and time-series forecasting to distribute bandwidth intelligently among different schools. The system gathers real-time bandwidth usage data, detects anomalies using the Interquartile Range (IQR) method, and predicts future demand through the Prophet time-series forecasting model. The allocated bandwidth is optimized based on these predictions, ensuring fair and efficient distribution among schools. The SDN-based load balancer also computes energy-efficient network routes to reduce congestion and enhance data flow efficiency. The solution provides a Streamlit-based interactive dashboard, allowing users to visualize bandwidth trends, monitor real-time allocations, and review detected anomalies. This approach ensures proactive network management, preventing bottlenecks and improving overall network performance.

The AI-Powered Personal Finance Assistant is a smart budgeting tool designed to help users gain control over their spending habits. Built with Streamlit, PyMuPDF, and the Deepseek V3 model (via Camel framework), this app analyzes transactions from uploaded credit card statements (PDFs). It categorizes expenses into needs, wants, and savings using the 50/30/20 rule and applies zero-based budgeting for smarter fund allocation. Additionally, it flags excessive spending patterns and offers actionable recommendations to improve financial habits. Key Features: ✅ AI-Powered Insights: Uses Deepseek V3 via Camel for personalized spending analysis with enhanced accuracy. ✅ Smart Budgeting: Applies the 50/30/20 rule and zero-based budgeting principles. ✅ Interactive Interface: Built with Streamlit for easy data uploads. ✅ Sample Data Support: Users can test the tool with sample statements provided. ✅ Actionable Recommendations: Provides clear steps to cut unnecessary expenses and save more. Tech Stack: Frontend: Streamlit Backend: Python (PyMuPDF, Camel framework) AI Model: Deepseek V3 Budgeting Principles: 50/30/20 Rule, Zero-based Budgeting Impact Statement: This tool empowers users with clear, actionable insights to build better financial habits, reduce overspending, and increase savings. It makes personal finance management accessible, intuitive, and data-driven, fostering long-term financial well-being.

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