A showcase of AI systems, production platforms, and open-source tools.
I'm a firm believer in learning by doing. This is a collection of my work, ranging from enterprise-grade SaaS platforms to experimental "from scratch" implementations.
AI-powered semantic document search platform using transformer embeddings and FAISS. Goes beyond keywords to understand meaning and context in your documents.
Enterprise multi-tenant SaaS platform for automated insurance loss run processing. Combines OCR and domain-specific LLMs to extract structured data from unstructured documents.
Production-ready recommendation engine using TF-IDF, SVD, and content-based filtering. Handles 930K+ movies with intelligent quality filtering, advanced features, and Django deployment.
Flask-based speech annotation platform for reviewing and correcting ASR transcripts with background jobs, row locking, and real-time progress tracking.
Educational repository implementing 18 essential ML algorithms from scratch using Python and NumPy. Features 2,500+ lines of documentation with mathematical foundations and production-quality code.
A small, self-hosted habit tracker. You run it on your computer, your data stays in a local SQLite file next to the app. The interface is a simple web app backed by a minimal Flask API.
Production-ready, local audio fingerprinting and song identification system inspired by Shazam. Uses spectral peak extraction and combinatorial hashing to identify songs from short audio clips in milliseconds.
A tool that transforms audio or video files into text transcripts and generates concise meeting minutes. Stay organized and efficient in your meetings, with Phase 2 enabling real-time transcription.
A modern, responsive portfolio website showcasing AI engineering projects and professional experience, with links to source code on GitHub.
A modern, AI-powered FIFA player recommendation system built with Flask and scikit-learn. Features separate models for male and female players with advanced search, similarity-based recommendations, and interactive comparisons.
A comprehensive, educational implementation of various autoencoder architectures for image processing — covering dimensionality reduction, reconstruction, denoising, similarity search, and image morphing.
A production-grade deep learning system for automated skin lesion classification using the HAM10000 dataset. Provides training, evaluation, and real-time inference for detecting seven types of skin lesions.
An open-source, interactive Python course that shows you what Python is actually doing under the hood — designed for developers who want to truly understand the language.
Interested in any of these projects or want to build something new together? I'm always excited to work on challenging problems.