Hi there 👋 I'm Taruma!

A Civil Engineer exploring the fascinating intersection of data, code, and AI. My passions range from applying data science and machine learning to hydrology and water resource management to delving into the world of Large Language Models (LLMs). I enjoy building tools, sharing knowledge, and collaborating with others.

🌱 Currently Exploring: Continuously learning and expanding my skillset in Python, data visualization, machine learning, deep learning, and Large Language Models (LLMs). I'm particularly excited about the potential of LLMs to transform how we interact with information and automate tasks.

👨‍💻 Featured Projects: Check out some of my open-source projects! Contributions, feedback, and collaboration are always welcome.

• hidrokit (Python Package): A Python package for hydrological analysis used in several of my web applications. It provides functionalities for various hydrological calculations.
• Web Apps for Rainfall Data Processing: Making rainfall data more accessible and insightful! This suite of web applications covers data acquisition, analysis, exploration, and frequency analysis. Built with Python and Dash frameworks.
  • fiako-stations: This app simplifies the exploration of daily rainfall data available in databases. It provides a user-friendly interface to search and discover relevant datasets for your specific needs. It's the starting point for your rainfall data journey! (Featured as a Plotly Geospatial App Example).
  • hidrokit-rainfall: Dive deeper into daily rainfall analysis with this interactive application. Explore data visually, perform calculations, and gain insights into rainfall patterns and trends. This app utilizes the hidrokit Python package for its core functionalities. (Featured as a Plotly Data Visualization & Dashboard App Example, and Plotly App of the Month).
  • fiako-anfrek: Focus on frequency analysis in hydrology with this specialized application. Compute statistical parameters, perform distribution fitting, and estimate rainfall extremes for various return periods. An essential tool for water resource management and planning. (Featured in Plotly & Dash 500 Index and Plotly App of the Month).
• feidlambda (Excel Lambda Functions): Supercharging Excel with custom functions! This collection simplifies working with dynamic arrays and provides tools for mathematical operations.
• Eurovision Song Contest Dashboard (R Shiny): Because data visualization can be fun too! This dashboard lets you explore Eurovision winners through the years.
• 🆕MTA Ridership Explorer: An interactive Dash-based visualization tool that tracks NYC's MTA ridership trends and recovery patterns across multiple transit modes with AI-powered insights.

🤝 Let's Collaborate! I'm eager to connect and collaborate on projects related to:

• Hydrology and Water Resources
• Data Visualization and Interactive Dashboards
• Open-Source Software Development
• Python and R Programming
• Large Language Models (LLMs) and Natural Language Processing (NLP)

❓ Ask Me About: Anything related to the topics above! I'm always up for a chat about Python, R, data science, machine learning, deep learning, hydrology, LLMs, or even the Eurovision Song Contest! I love sharing what I've learned and learning from others.

📫 How to Reach Me: hi@taruma.info or connect with me on LinkedIn!

⚡ Fun Fact: My rainfall data processing web apps have been featured by Plotly (Apps of the Month, Plotly & Dash 500 Index).