Project Overview

This comprehensive aviation analytics dashboard was developed to help airlines optimize their operations through data-driven insights. The project involved analyzing massive datasets from multiple sources including flight schedules, weather data, and maintenance records.

Key Features

• Real-time flight tracking and delay prediction
• Weather integration for route optimization
• Predictive maintenance scheduling
• Cost analysis and savings calculator
• Interactive visualizations with Tableau

Technical Implementation

Built using Python for data processing, with pandas and numpy for analysis. The dashboard was created in Tableau with custom SQL queries for data extraction. Machine learning models were implemented using scikit-learn for predictive analytics.

Project Overview

A machine learning project that analyzes historical movie data to predict box office success and identify key factors that contribute to a film's commercial performance.

Machine Learning Models

• Random Forest for feature importance analysis
• Linear Regression for box office prediction
• Clustering analysis for audience segmentation
• Sentiment analysis of reviews and social media

Project Overview

A fully responsive personal portfolio website showcasing web development skills and design expertise. Built from scratch with modern web technologies to create an engaging user experience that effectively presents professional work and capabilities.

Key Features

• Responsive design optimized for all devices
• Smooth CSS animations and transitions
• Interactive project showcase with filtering
• Contact form with validation
• SEO optimized with meta tags
• Fast loading times and performance optimization

Technical Implementation

Built with HTML5, CSS3, and vanilla JavaScript. Utilized CSS Grid and Flexbox for responsive layouts. Implemented smooth scrolling, lazy loading for images, and optimized assets for fast performance across all devices.

Project Overview

An advanced analytics dashboard that predicts customer churn probability and identifies at-risk customers using machine learning algorithms. The system provides actionable insights to help businesses implement targeted retention strategies.

Key Features

• Real-time churn risk scoring and alerts
• Customer segmentation and behavior analysis
• Interactive visualizations with drill-down capabilities
• Automated reporting and email notifications
• ROI calculator for retention campaigns
• Historical trend analysis and forecasting

Technical Implementation

Built with Python using pandas for data manipulation and scikit-learn for machine learning models. The dashboard was created using Plotly Dash with interactive visualizations. PostgreSQL database for data storage with automated ETL pipelines.

Project Status

Currently developing a modern e-commerce platform with focus on user experience, performance, and scalability...

Completed Features

• User authentication and authorization
• Product catalog with search and filtering
• Shopping cart and wishlist functionality
• Responsive design for all devices

Upcoming Features

• Payment gateway integration
• Order management system
• Analytics dashboard
• Admin panel for inventory management

Project Overview

Comprehensive financial data analysis project for Krom Bank...

Analysis Areas

• Customer segmentation and lifetime value analysis
• Credit risk assessment and fraud detection
• Transaction pattern analysis and anomaly detection
• Market basket analysis for cross-selling opportunities

Technical Implementation

Utilized Python with pandas, numpy, and scikit-learn for data analysis...