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Hi! My name is Ed, and I'm currently a machine learning 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, mainly using it for machine learning or data related things, as well as any general purpose scripting, task automation or web development.

I did my fair share of Ruby development back in the day, and I am also familiar with the use of R for applied statistics, but lean heavily towards Python.

Edwin (Ed) Onuonga's Projects

arx icon arx

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

daze icon daze

Better multi-class confusion matrix plots for Scikit-Learn, incorporating per-class and overall evaluation measures.

dotfiles icon dotfiles

My personalised dotfiles for macOS - mostly Git aliases, Ruby scripts and ZSH configurations.

eonu.github.io icon eonu.github.io

Collection of personal notes, notebooks, documentation and other resources.

feud icon feud

Build powerful CLIs with simple idiomatic Python, driven by type hints. Not all arguments are bad.

goldfish icon goldfish

Pixel-style sans-serif font faces (Volter & Volter-Bold) designed by Sulake.

mytex icon mytex

Useful mathematical shortcuts/commands for LaTeX.

opacus icon opacus

Training PyTorch models with differential privacy

pytorch-lightning icon pytorch-lightning

Pretrain, finetune and deploy AI models on multiple GPUs, TPUs with zero code changes.

sequentia icon sequentia

Scikit-Learn compatible HMM and DTW based sequence machine learning algorithms in Python.

tooltip icon tooltip

Pure SCSS pseudo-element tool-tip configured with custom HTML attributes.

torch-fsdd icon torch-fsdd

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

torchmetrics icon torchmetrics

Torchmetrics - Machine learning metrics for distributed, scalable PyTorch applications.

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