This repository is the personal website and research blog of Teddy Koker. It is built with Jekyll and hosts a collection of in-depth technical blog posts, primarily centered on machine learning, algorithmic trading, and computational science. The core content consists of Jupyter notebooks that have been converted into Jekyll posts, covering topics such as reinforcement learning for trading, neural machine translation with attention, survivorship bias in financial datasets, and neural variational Monte Carlo for quantum chemistry. The repository functions as a hybrid between a static site and a data research portfolio. The Jekyll framework provides the presentation layer, while the `_notebooks/` directory contains the primary research artifacts. The site includes custom layouts, a bibliography management system via `jekyll-scholar`, and a sophisticated pipeline (`_notebooks/jekyll.py`, `convert.sh`) for transforming Jupyter notebooks into publishable blog posts with proper front matter and image handling. While the Jekyll site is well-maintained and reproducible, the Python research notebooks exhibit significant technical drift. They rely on deprecated APIs (e.g., `torchtext` legacy, `pandas_datareader` Yahoo Finance) and lack a pinned Python environment, making exact reproduction challenging. Despite this, the repository is a valuable resource for learning about applied ML and quantitative finance, and several components (the notebook conversion pipeline, the attention module, the backtesting wrapper) are genuinely reusable.