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    Featured Projects

    Explore our collection of open source projects and find the perfect opportunity to contribute

    Lead Score Model (LSM) Introduction

    A systematic approach to evaluate and rank potential customers based on their likelihood to convert into paying customers.

    • Implemented demographic data analysis (age, gender, location)
    • Developed behavioral tracking system
    • Created firmographic data integration
    • Built engagement level scoring system
    • Integrated transactional data analysis
    • Designed point assignment mechanism
    • Implemented automated scoring updates
    • Created performance monitoring dashboard
    • Developed API for CRM integration
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    Recommendation Engine with Big Data Framework

    Advanced recommendation system using PySpark and machine learning to enhance product discovery and user experience.

    • Implemented PySpark for large-scale data processing
    • Integrated with Jupyter Notebook and Google Colab
    • Developed personalized recommendation algorithms
    • Created attribute-based filtering system
    • Built real-time processing pipeline
    • Implemented user preference learning
    • Designed scalable architecture
    • Created performance monitoring tools
    • Developed API endpoints for integration
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    Insurance Policy Management System

    AI-powered platform for streamlining insurance operations and claims processing.

    • Developed with Angular and Spring Boot
    • Implemented AI-driven claims processing
    • Integrated secure document storage with S3
    • Automated testing with Selenium
    • Created automated email notification system
    • Implemented machine learning for policy personalization
    • Developed real-time monitoring dashboard
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    Algorithmic Trading Using Statistical Models

    Interactive dashboard for analyzing Apple Inc. (AAPL) stock data using statistical models and predictive analytics.

    • Built interactive dashboard for AAPL stock trends visualization
    • Implemented trend analysis with moving averages
    • Created volume and price fluctuation tracking
    • Developed user-adjustable date ranges and metrics
    • Integrated moving average indicators
    • Built performance insights dashboard
    • Implemented entry/exit point identification
    • Created timeframe-specific analysis tools
    • Developed Streamlit-based user interface
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