FxNorm-Automix - Implementation of automatic music mixing systems. We show how we can use wet music data and repurpose it to train a fully automatic mixing system

Term Project repository for System Analysis and Design course in ITM, Seoultech.

A utility for defining metadata for data types and formats.

I made various data normalization operations with python scripts. Target data in CSV format

A production-ready serverless pattern for intelligent data normalization using Claude Haiku via AWS Bedrock

This project predicts used car prices using a feedforward neural network regression model implemented in PyTorch. Features include car age, mileage, and other attributes. The pipeline supports feature normalization, train/validation/test splitting, and visualization of training and validation loss curves.

Developed a Python-based web scraper leveraging generative AI with LangChain and GPT-4o-mini to extract and classify FDA drug approval data. Processed over 1,770 records, dynamically categorizing medications and treatment areas using LLMs to simplify complex medical information into actionable insights.

A large pile of interesting and/or useful information

Clinical Decision Support System (CDSS) for Emergency Triage. Python implementation of regional healthcare protocols featuring complex logic, input normalization, and automated clinical pathways

🌟 Fraud Detection in Application 🌟 Through Isolation Forest and K-Means Clustering, the project detects suspicious patterns like inconsistent income, duplicate entries, and unrealistic employment data. This end-to-end workflow transforms raw data into actionable fraud insights — enhancing trust and accuracy.

A collection of bioinformatics and data mining scripts

A Streamlit-based clinical decision-support demo showcasing data cleaning, normalization, rule-based recommendation logic, and workbook-driven pipeline design.

Python project

An enterprise-grade Universal Credit Risk Assessment Platform. Features a calibrated ML Ensemble (LightGBM/XGBoost/CatBoost) with 0.86 ROC-AUC, dynamic dataset mapping/normalization, Risk Signal Engine (SCQS), Explainable AI (SHAP), auto-generated PDF underwriting reports, and a premium React What-If simulator dashboard.

This project focuses on creating a simple data warehouse using SQLite. It includes scripts for table creation, data loading, and querying the database, providing a foundational understanding of data warehousing concepts. This project is ideal for those interested in database management and data retrieval.

Data transformation toolkit — standardize, reshape, and normalize messy data. Python & TypeScript. 83 transforms, zero-config mode, MCP server, edge-safe. DQBench 100/100.

govaitextextract extracts structured AI/tech initiative data from text for policy, news, and recruitment analysis.

Feature wise normalization: An effective way of normalizing data

Data cleaning and preprocessing of the Netflix titles dataset using Python and Pandas. Tasks included handling missing values, removing duplicates, normalizing categorical data, and preparing the dataset for further analysis.

✨ Stock Price Prediction Using Tesla Dataset ✨ In this project, I analyzed Tesla’s historical stock data to forecast future closing prices using machine learning models like Random Forest Regressor. Through data cleaning, feature engineering, and rich visual analytics, I explored patterns in price trends, volatility, and trading volume.