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slee7286/README.md

Hi there, I'm Siheon 👋

GitHubProjectsCourseworkCurrent Work


About Me

  • I am a student at Imperial College London studying Economics, Finance and Data Science.
  • I work through advanced ML/AI coursework and hands‑on projects (e.g. Stanford CS229 / CS224N style material).
  • I enjoy building end‑to‑end data workflows: from exploratory notebooks to deployable code.
  • I like experimenting with new tools and editors.

🎯 Projects

Mini-GPT with Rotary Embeddings

Developed a compact GPT‑style language model inspired by Karpathy’s minGPT and pre‑trained it on the Wikipedia corpus. Incorporated rotary positional embeddings (RoPE), achieving a 2.3× improvement in benchmark performance compared to a baseline model using standard positional embeddings.

➡️ Repo: Mini-GPT

Cherokee–English Seq2Seq NMT Model

Designed a neural machine translation system with a bidirectional LSTM encoder and unidirectional decoder, achieving BLEU 11.77 on the Bible corpus, demonstrating ability to handle low-resource languages.

➡️ Repo: Cherokee-English Machine Translation

Global GDP & Youth Employment Data Analysis

Built end-to-end data pipelines in R using multi-source World Bank and custom datasets, delivering statistical EDA and visual analytics to quantify links between GDP growth, youth employment, and human development.

➡️ Repo: World Bank Data Analysis Project


🎓 Coursework

Course Description
Stanford: Machine Learning Introduction to machine learning and statistical pattern recognition
Stanford: Natural Language Processing with Deep Learning Fundamentals of natural language processing (NLP) and language models using Pytorch framework
Stanford: Reinforcement Learning Main approaches and challenges in reinforcement learning
Imperial: Year 1 Trimester 1 Mathematical Foundations, Probability and Statistics, Introduction to Data Science, Big Issues in Economics and Finance

These repos show my coding work, notes (in LaTeX), implementations, and experiments.


📚 Current Work

  • Advanced machine learning and optimization techniques.
  • Modern NLP (transformers, attention, representation learning).
  • Better software engineering practices (testing, structure, reproducibility).
  • Improving my C++, Python, and Javascript skills for production‑ready apps.
  • Work on redeveloping the backend of Imperial College London Rocketry's Pickle board.

🧩 Tech I Use

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  1. JPMorgan-Apple-Challenge JPMorgan-Apple-Challenge Public

    Python

  2. Module_Work Module_Work Public

    HTML

  3. XCS234-Work XCS234-Work Public

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  4. XCS224N-Work XCS224N-Work Public

    Jupyter Notebook

  5. eth-oxford-26-submission eth-oxford-26-submission Public

    TypeScript

  6. hackeurope2026 hackeurope2026 Public

    TypeScript