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matin kaffashian
developerAI Engineer | RAG & AI Agents | Python, FastAPI, PyTorch | OCR & Computer Vision | Open to fully remote roles
Public projects
-Fetal-Planes-Classification-using-EfficientNetV2-S-PyTorch-
A deep learning project for classifying fetal ultrasound images into 6 anatomical planes using EfficientNetV2-S and PyTorch. Includes full training pipeline, data preprocessing, transfer learning, and evaluation achieving 90%+ accuracy on the Fetal Planes Dataset.
Jupyter Notebook
FloodHazardPrediction-GIS-ML
This project detects and models flood risk areas using Sentinel-1 imagery, DEM data, and machine learning (Random Forest, XGBoost). It includes feature extraction, shapefile-based labeling, model evaluation, and generates flood hazard maps for GIS visualization.
deep-learning-Chest_X_Ray_Images_Pneumonia
This project uses deep learning techniques to classify chest X-ray images into two categories: Pneumonia and Normal. A Convolutional Neural Network (CNN) is trained and evaluated on a dataset of X-ray images to detect pneumonia with high accuracy.
Jupyter Notebook
classification_income_ML
The "classification_income_ML" project uses machine learning to predict individuals' income levels based on demographic and socio-economic data. It aims to identify key factors influencing income disparities.
Jupyter Notebook
Likely stack
PyTorchFastAPI
