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eonu/README.md

👋

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

Pinned

  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
    2
    
                  
    3
    class NBX
    4
      # Execute long-running Jupyter notebooks from the command-line
    5
    
                  

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/eonu.github.io and 2 other repositories

Contribution activity

December 2022

3 contributions in private repositories Dec 1 – Dec 5

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