Breast Cancer Classification (AI)
Developed deep learning models (DenseNet, EfficientNet, VGG16) for breast cancer diagnosis with Grad-CAM heatmap visualization.
GithubHere’s a selection of my projects in AI, data science, and web development — showcasing both technical skills and real-world impact.
Developed deep learning models (DenseNet, EfficientNet, VGG16) for breast cancer diagnosis with Grad-CAM heatmap visualization.
Github
Created preprocessing and training pipelines for 3D CNNs using MONAI and PyTorch, improving classification of lung cancer from DICOM scans.
Github
Built a multi-agent system for e-commerce using LLMs, sentiment analysis, scraping, and trend detection with LangChain orchestration.
Github
This repository includes training and evaluation of multiple neural network architectures for animal classification, such as: AlexNet, ShuffleNet, EfficientNet
Github
Real-time environmental sound recognition using deep learning for edge deployment.
Github
Real-time environmental sound recognition using deep learning for edge deployment.
Github
This repository includes training and evaluation of multiple neural network architectures for animal classification, such as: AlexNet, ShuffleNet, EfficientNet
Github
This repository includes training and evaluation of multiple neural network architectures for animal classification, such as: AlexNet, ShuffleNet, EfficientNet
Github