Impress your boss with interactive Decision Tree visualization
NeLux: High-performance video processing for Python, powered by FFmpeg and PyTorch. Ultra-fast video decoding directly to tensors.
Screw type detection using ESP-EYE, YOLOv5, and TensorFlow Lite Micro for real-time classification on ESP32.
This repository contains a collection of simple yet insightful Data Science projects that showcase my ability to apply analytical thinking, build ML models, and visualize results.
Decision Tree are the typically machine learning algotithm that are work on specific data and generate the tree with yes or no formate.
Open-sourced is_even function powered by LLM
AI/ML Engineer Portfolio | Japanese RAG Production System (FastAPI + real evaluation) | Credit Card Fraud Detection (XGBoost + SHAP + Docker) | Japanese Sentiment Analysis (BERT) | Targeting mid-level roles in Japan
Real-time cardiovascular risk prediction platform built with Next.js, Flask, and a robust ML pipeline.
End-to-end ML project predicting household energy consumption | EDA → Preprocessing → XGBoost | R² 89.4% | Python, scikit-learn, XGBoost
morphogenetic language systems
Forging a cutting-edge Salary Prediction Software for Software Engineers. Seamlessly blending the art of data science and the precision of machine learning.
AI-Powered Medical Image Diagnosis Platform | FastAPI, Next.js, MobileNetV2, Secure Reports, HIPAA-Compliant
✨ Special repository: My professional Data Science portfolio and AI journey.
MediGuide is a machine learning-based medical recommendation system that leverages Support Vector Machines (SVM) to provide intelligent health suggestions. Built using Python, Flask, and Scikit-Learn, this project predicts potential medical conditions based on user inputs and offers relevant recommendations.
Autonomous multi-agent AI for literature discovery, citation graph analysis, ML experiments, and research report generation.
An NLP project that discovers hidden topics in news articles using unsupervised topic modeling, text preprocessing, keyword extraction, and document clustering techniques.
Credit risk assessment system predicting loan defaults using Logistic Regression, Random Forest, and XGBoost. SMOTE for class imbalance, SHAP for per-prediction explainability, and a multi-page Streamlit dashboard. Built on Lending Club data.
eal-time financial dashboard using Random Forest to predict 5-minute market movements. Built with Python, Scikit-Learn, and Streamlit.
AI/ML-powered exoplanet detection system using NASA Kepler, K2, and TESS mission datasets.
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