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tdr24008/README.md

👋 Hi, I'm Tom Richardson


🚀 Current Focus

  • 🤖 2+ years working for Viewerslogic as a Data & Machine Learning Engineer
  • ♟️ Co-founder of ChessCam - turning real boards into digital notation
  • 📚 Studying MSc in Machine Learning & Data Science at Imperial College London
  • 🛠️ Building AI-first side projects as why not

🧠 Technical Interests

  • Bayesian modeling & variational inference
  • Causual Inference, espcially within Media analysis
  • Automated reasoning & probabilistic programming
  • Full-stack ML: from notebook to MLOps

☁️ Fun Facts

  • I love running, playing chess, and learning about theology.

Pinned Loading

  1. Economist-AgentEconomist-AgentPublic

    Economist Agent built with Streamlit and Autogen. Runs fully local with Ollama for secure LLM inference. Features a Data Analyst agent for economic reasoning and a Code Executor agent in a sandbox …

    Python 1

  2. ChessCamChessCamPublic

    Forked from Pbatch/CameraChessWeb

    Record a chess game live and upload the PGN to Lichess

    TypeScript

  3. Multi-Armed-Bandit-Movie-RecommenderMulti-Armed-Bandit-Movie-RecommenderPublic

    Built a contextual bandit recommender using MovieLens, implementing ε-greedy, UCB, LinUCB and Thompson Sampling. Simulated user-item rewards, evaluated cumulative regret and convergence, and showed…

    Jupyter Notebook

  4. langchain-scalekit-task-agentlangchain-scalekit-task-agentPublic

    This project is a simple conversational AI agent that demonstrates how to integrate ScaleKit with LangChain and deploy it in a Streamlit web app.

    Python

  5. Churn-analysisChurn-analysisPublic

    Whilst at Viewerslogic, I led a project looking at our panellists data and identifying key features that would predict whether they churned after a number of weeks. This heavily involved feature en…

    Jupyter Notebook

  6. EDA_London_schoolsEDA_London_schoolsPublic

    Within the Explorartory Data Analysis (EDA) & Visualisation module during my masters, we had to do an EDA on a London Schools data. During this, I thoroughly cleaned the data, explored clustering i…

    R