AI & Machine Learning

Rock Paper Scissors played with real hand gestures via webcam. MediaPipe detects hand landmarks in real time; an adaptive Markov chain CPU opponent learns from your play patterns and adjusts strategy mid-game.

Six interactive machine learning demos running entirely in the browser — neural networks, tokenizers, embeddings, regression, activation functions, and attention mechanisms. No server, no backend; all compute is client-side.

Graph-based image segmentation implemented from scratch. Models an image as a weighted undirected graph — each pixel a node, edges weighted by color similarity. Union-Find (with path compression + union-by-size) merges the most similar pixels first. Tunable k, σ, and min_size parameters give coarse-to-fine control over segmentation granularity.

End-to-end ML pipeline for credit scoring on real fintech loan data. Feature engineering, model selection (XGBoost, LightGBM), MLflow experiment tracking, and a FastAPI inference endpoint.

Churn prediction system with class-imbalance handling (SMOTE), SHAP explainability, and a Dagster orchestration pipeline pulling from PostgreSQL via dbt-transformed tables.

Real-time fraud detection using transaction sequence features, geospatial signals, and an ensemble model. Includes a streaming-friendly inference layer and anomaly scoring dashboard.

Multi-horizon demand forecasting pipeline over financial telemetry data. Compared ARIMA, Prophet, and LSTM approaches with automated retraining on drift detection.

Text classification and entity extraction pipeline for financial documents. Fine-tuned a transformer model for Amharic-English mixed text and deployed with a FastAPI wrapper.