I'm a developer interested in:

• 🧠 AI, Databases, Machine Learning
• ⚙️ Building cool things with [tech stack]
• 🚀 Learning fast & shipping projects

AI-powered semiconductor wafer defect detection with multi-class classification, real-time analytics, and explainability. 🎯 Multi-Class Detection: 4 defect types (Normal, Scratch, Spot, Crack) 🔥 GradCAM Heatmaps: Visual defect localization 📊 Real-Time Analytics: Live statistics and trend charts 🗄️ Database Integration: SQLite prediction history 📦 Batch Processing: Analyze up to 20 images at once 📄 PDF Reports: Professional quality reports 🐳 Docker Ready: Containerized deployment

🔗 https://github.com/poprostujoachim/wafer-defect-detection.git

A machine learning-based music recommendation system that suggests similar songs based on audio features from Spotify dataset. Cosine Similarity: Recommends songs based on feature vector similarity Clustering-Based: Groups similar songs using K-Means clustering Feature Engineering: Analyzes genre, tempo, energy, danceability, and more Interactive Dashboard: Streamlit web interface for exploring recommendations

🔗 Link

• Languages: Python / C++ / SQL
• Tools: Git, Docker
• Currently learning: JavaScript

• LinkedIn: Link

"Build things. Break things. Learn fast."