From computer vision pipelines to RAG chatbots and MLOps infrastructure — engineered for production, not just notebooks.
Problems, architectures, and production thinking — not just code.
Production financial system for a health-worker cooperative. Double-entry accounting, automated batch processing, five user roles, and legacy Excel migration — deployed on-premise via Docker.
End-to-end ML pipeline for BUY/SELL signals on 45 IDXBLUE stocks — MLflow tracking, Grafana monitoring, Docker deployment, automated retraining.
Detect-then-classify architecture for high-accuracy object recognition. YOLO/SSD detection + custom PyTorch classifiers — optimized for edge deployment.
Retrieval-Augmented Generation chatbot answering questions about my CV. LangChain LCEL + FAISS + FastEmbed (ONNX) + Groq Llama 3.3, evaluated with RAGAS metrics.
Playwright-based scraper that automatically searches for 2,500+ product images across 4 Indonesian e-commerce platforms — with anti-bot evasion, scheduled runs, and resume support.
AI-driven chess variant exploring state-space search, evaluation heuristics, and interactive game design patterns — Minimax with Alpha-Beta pruning.
The gap between a Jupyter notebook and a production system is where most ML projects fail. I build systems with monitoring, evaluation pipelines, and clean architecture from day one.
Whether it's a cooperative's accounting software or a stock prediction pipeline — the standard is the same: ship it, measure it, improve it.
Read my full approach →A live demonstration of Retrieval-Augmented Generation — ask anything about my background, skills, and projects. Built with LangChain + FAISS + Streamlit.
Technical deep-dives on ML engineering, MLOps, and building in production.
RAGAS evaluation, retrieval metrics, and why "it works on my machine" isn't enough for production LLM systems.
June 2024Why splitting detection and classification into two stages gives you better accuracy, maintainability, and deployment flexibility.
May 2024Running MLflow, Grafana, and Docker on modest hardware. Pragmatic MLOps for solo engineers and small teams.
April 2024