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This project represents a complete ML engineering journey, evolving from experimental hand detection to a production-ready system. Built on YOLOv8 architecture and trained on a custom dataset of 1,740 manually curated images, the model achieves 96% accuracy in distinguishing between hands, arms, and non-hand objects. The system features real-time inference at 30+ FPS, seamless web integration via Vercel AI SDK, and deployment on HuggingFace Spaces for universal access.
Started with ML-Visions FinetuneWorkshop: Halloween Hand Detection project - a 15-minute workshop for fine-tuning YOLOv8 to build a binary hand detection classifier with automated dataset creation
Abstracted learnings into the ML Training Pipeline project - a flexible machine learning training pipeline supporting multiple models (YOLO, TensorFlow, PyTorch) with deployment options to Hugging Face and RunPod
Started hand-sign-detection with cleaned ML template
Integrated 867 images from ml-visions, expanded to 1,344
Added arm detection for better hand distinction
Deployed to HuggingFace with Vercel AI SDK integration
Enterprise-grade AI-powered recruitment platform with voice interviews, resume screening, multi-channel communication, and seamless ATS/HRIS integrations. Automates hiring workflows for Quick Service Restaurants, healthcare, and construction industries.
Local-first memory layer for AI coding agents. 14 MCP tools, 268K+ indexed chunks, hybrid semantic+keyword search, local LLM enrichment. pip install brainlayer.
Local voice input/output layer for Claude Code. 7 MCP tools, 5 voice modes, whisper.cpp STT (~300ms), edge-tts, session booking. bunx voicelayer-mcp.
A comprehensive e-commerce platform for handmade candles featuring a React-based storefront with shopping cart, favorites, filters, and a Node.js backend with MongoDB. Fully responsive design with admin dashboard for order management.