Skip to content
Block or Report

Block or report eonu

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse


Hi! My name is Edwin, and I'm currently an ML engineer at Hazy working on improving a privacy-preserving synthetic data generation platform for enterprise data analytics.

I studied at the University of Edinburgh, with an MSc in Statistics with Data Science at the School of Mathematics, and a BSc in Computer Science at the School of Informatics.

I normally work with Python, R and sometimes Ruby, mainly doing machine learning or data science related things in Python and R, and any general purpose scripting, task automation or web development in Python and Ruby – but I'm always interested in learning new things!

Right now, I'm learning about:

  • Docker and containerisation
  • Gaussian processes
  • AWS services

I'd like to learn more about:

  • C++
  • Graphs: general graph theory concepts, spectral graph theory, graph ML
  • Bayesian methods: variational inference, probablistic graphical models, Bayesian optimization
  • Statistical time series: autocorrelation, forecasting models (ARIMA, GARCH etc.)
  • Ensemble classifiers: bagging and boosting (with AdaBoost, XGBoost, LightGBM etc.)

I'm very familiar with:

  • Common ML methods: GLM, logistic regression, kNN, mixture models etc.
  • Neural networks: mainly feed-forward and recurrent architectures, but also some knowledge and practice with CNNs
  • Sequential modelling: HMMs, RNNs, DTW
  • Natural language processing: word embeddings, attention, sentiment analysis
  • Statistical methodology: likelihood-based inference (MLE, CIs, etc.), Bayesian statistics, hypothesis testing

I am confident with these languages, tools and systems:

Python Ruby R PostgreSQL HTML JavaScript CSS SASS
VS Code RStudio Git   GitHub MacOS Bash Conda LaTeX


  1. sequentia Public

    HMM and DTW-based sequence machine learning algorithms in Python following an sklearn-like interface.

    Python 47 7

  2. arx Public

    A Ruby interface for querying academic papers on the arXiv search API.

    Ruby 28 1

  3. torch-fsdd Public

    A utility for wrapping the Free Spoken Digit Dataset into PyTorch-ready data set splits.

    Python 6 1

  4. 1
    #!/usr/bin/env ruby
    class NBX
      # Execute long-running Jupyter notebooks from the command-line

593 contributions in the last year

Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Mon Wed Fri
Activity overview
Contributed to eonu/sequentia, eonu/eonu, eonu/ and 2 other repositories

Contribution activity

December 2022

3 contributions in private repositories Dec 1 – Dec 5

Seeing something unexpected? Take a look at the GitHub profile guide.