Projects

AI/ML/MLOps

Sample ML model API following the Open Inference Protocol

  • Designed following the Open Inference Protocol — a growing industry standard for standardized, observable, and interoperable machine learning inference

    • Tech: scikit-learn, FastAPI, pytest, pre-commit, Docker, Github Actions, Pydantic

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    MLOps 101 Project for a mini-course I teach

  • After learning a tonne from great online teachers, and projects I decided to transfer my knowledge onto undergraduate students who are curious about the life of a model outside the Jupyter notebook
  • An end-to-end ML system that processes taxi data, stores models in a model registry, exposes them via an API, and deploys this API to Google Cloud, and keeps logs for observability

    • Tech: scikit-learn, EvidentlyAI, FastAPI, MLFlow, Docker, Github Actions, Terraform, Google Cloud (GCS, Logging, Compute Engine, Artifact Registry, Kubernetes Engine)

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    MLOps Architecture for Real-Time Fraud Detection

  • An AI-driven solution for real-time credit card fraud detection using MLOps techniques
  • Fully orchestrated pipelines, including data ingestion, model training, and real-time prediction and monitoring
  • High fraud case detection through Graph Convolutional Network, XGBoost, and CatBoost models

    • Tech: Neo4j graph DB, Sklearn, PyG, Mlflow, Kafka, Grafana, Mage orchestration, Docker, Streamlit

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    Voice-to-Voice Personal Finance Assistant

  • Talk, Learn and Analyse your spending habits with your Personal Finance Assistant AI Agent. Communicate through speech
  • Frontend + Backend communicating via a websocket
  • Ask follow-up questions (the language model can see the chat history)
  • Detailed observability of live and historical connections to the server via Pydantic Logfire

    • Tech: Webhooks, FastAPI, PydanticAI, Logfire, SQLite, OpenAI, Ollama, PostgreSQL, React

    View on GitHub

    MLOps Architecture for Insurance Fraud Detection

  • Building an end-to-end MLOps pipeline to detect car insurance fraud
  • Pipeline orchestration covering data storage, data preprocessing (using IV and WoE), model training, deployment, and monitoring
  • Focus on achieving high recall in fraud detection using a Balanced Random Forest Classifier

    • Tech: PostgreSQL DB, Terraform, Google Cloud Platform, Mlflow, Prefect, Grafana, Evidently, Docker, FastAPI

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    Other AI/ML

    Notebook Expert on Kaggle

    Diving into the full story behind multicollinearity

    LingoMate - hackathon project for language learners

    Doing a neural network epoch+math by hand

    text2chart - transforming natural language to charts

    PDF RAG from scratch

    Using Video Generation Models for Taxi OD Demand Matrix Predictions

    db2chat - chat with your (SQLite) database

    Data Eng

    Esports Voice Data Pipeline (Zach Wilson's DE bootcamp capstone)

  • Esports team communication data is normally kept private, but for the first time a team is sharing their full voice communication records so with this I am showing a prototype of a pipeline that utilises audio data to extract communication patterns
  • In addition, I developed visualizations that uncover communication patterns and dynamics, providing the underlying team with actionable insights to enhance their gameplay

    • Tech: Airflow, dbt, Google BigQuery, Google Cloud Storage, Streamlit, Terraform, Github Actions, Astronomer

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    Write-Audit-Publish exercise YT video

  • Recorded a youtube tutorial on how to follow the WAP DQ practice using popular tech

    • Tech: Dremio, Apache Iceberg, Nessie, MinIO

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    EU AI Act Graph Modelling

  • Scraped the EU AI Act website and created a conceptual, logical and a physical data model, improving my understanding of the Act’s requirements
  • Separated entities into Articles, Recitals, Annexes, Chapters, Versions, Summaries and implemented the physical model using a graph database

    • Tech: Python, Neo4j, BeautifulSoup

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    Transaction Stream Data Engineering Pipeline

  • Generate transaction data via Stripe's API
  • Stream data using Apache Kafka and process it in real-time with PySpark Structured Streaming
  • Store processed data in PostgreSQL
  • Manage data transformations and modeling using dbt
  • Visualize data using Grafana

    • Tech: PostgreSQL DB, Kafka, PySpark, dbt, Grafana

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    Glaswegian Audio Dataset and ASR model

  • Co-create a 120 minute open-sourced Glaswegian dataset
  • Preprocess raw audio and transcriptions and upload to HuggingFace
  • Research into audio AI models and fine-tune ASR and TTS models

    • Tech: HuggingFace, Python, Fine-Tuning, Audio AI

    View on HuggingFace

    Lending Club Data Engineering Pipeline

  • Build a data pipeline to process and visualize Lending Club data
  • Extract raw data from Kaggle and load it into Google Cloud Storage
  • Process data with dbt in BigQuery
  • Create visualizations using Looker
  • Manage infrastructure with Terraform
  • Orchestrate the entire process with Mage

    • Tech: Docker, Mage orchestration, Google Cloud Platform, Terraform, dbt, Looker

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    Web/API/Other

    RSS Aggregator API

  • Developed an API that allows users to authenticate, scrape RSS feeds, follow feeds of their choice, and view posts from those feeds
  • The API is fully tested, dockerized, and available on Docker Hub
  • Deployed the API in a local Kubernetes setup with dashboards for monitoring both Kubernetes and the API

    • Tech: Go, PostgreSQL, GitHub Actions, Docker, Kubernetes, Prometheus, Grafana

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    Platform Engineering with Backstage

  • Built and deployed a Python API, created CI/CD pipelines with GitHub Actions, Helm, and ArgoCD for streamlined Kubernetes deployments
  • Registered components in Backstage’s software catalog, managed team ownership, published TechDocs, and deployed Backstage in production using Docker & Kubernetes

    • Tech: GitHub Actions, Docker, Kubernetes, ArgoCD, Helm, Backstage

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    Sample ML model API following the Open Inference Protocol

  • Designed following the Open Inference Protocol — a growing industry standard for standardized, observable, and interoperable machine learning inference

    • Tech: scikit-learn, FastAPI, pytest, pre-commit, Docker, Github Actions, Pydantic

    View Project

    politics.news - TUI for reading political news from the terminal using Go

    Webapp for classifying hand-written Hangul characters

    RESTful Node.js/Express backend for a restaurant review application

    Webapp to Practice Hanja Characters for Hanja Exam

    Created a quiz webapp with custom questiones on general topics

    Discord bot for audio transcriptions