🎛 A comprehensive suite of DSP challenges featuring Image Restoration (Notch/Blur) and Audio Analysis (IIR/LPC). Built with Python 3.14 + uv for high-performance signal processing.
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Updated
Jan 1, 2026 - Python
🎛 A comprehensive suite of DSP challenges featuring Image Restoration (Notch/Blur) and Audio Analysis (IIR/LPC). Built with Python 3.14 + uv for high-performance signal processing.
BCG Adverse Event Severity Predictor : This project provides a web app built with Flask to predict the severity of adverse events after BCG vaccination. It uses a trained machine learning model to assist healthcare professionals in early identification and management.
A lightweight research-oriented project analyzing how noise, missing values, and corrupted features affect machine learning model reliability. Includes synthetic data generation, multi-model training, and noise-impact evaluation with visualization. Designed as a teaching/learning artifact for data quality, robustness, and ML reliability concepts.
🔍 Analyze how noisy and incomplete data impacts machine learning model performance on binary classification tasks with robust evaluation methods.
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