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Hello! 👋

My name is Josef Ondrej and I enjoy building useful mathematical and machine learning models.

I have a solid background in mathematics ➗, particularly in statistics and probability theory, from my studies at the Charles University in Prague. But besides solving math problems I also certainly do not shy away from scraping data, digging into it and writing well tested ✅ production code with CI/CD pipelines and monitoring 🖥 -- skills that I gained while developing and operating the Watson Assistant Autolearn feature at IBM.

I also spent a couple of years promoting the use of MLOps at sports betting company ⚾ Tipsport mainly using Jenkins, Docker, OpenShift, ArgoCD, MLFlow and Helm Charts while also developing models for predicting sports matches outcomes in Tensorflow and PyTorch.

My language of choice is Python 🐍 (in which I developed a few small libraries and projects like Snax, Transplants, SVGecko, API-Watchdog and GlucoScan) but I have also worked a lot with Java and have some experience also with R, JavaScript, Groovy (for Jenkins plugins), C# and a few others. I can also manage some basic web development (React, HTML, CSS) if needed.

In my free time I enjoy climbing and hiking in the mountains ⛰️.

For more information you can check out my CV or website or feel free to contact me.

Josef Ondrej's Projects

advanced-r icon advanced-r

My notes and exercises from the great book Advanced R by Hadley Wickham

censorship icon censorship

Small fun language modelling project to hide messages in other messages

deepstack-leduc icon deepstack-leduc

Example implementation of the DeepStack algorithm for no-limit Leduc poker

garl icon garl

GRAPH ATTENTION REINFORCEMENT LEARNING

glme-in-r icon glme-in-r

Few examples on how to fit generalized linear models in R

image-annotator icon image-annotator

Small utility for quickly annotating coordinates of a single object on images

intent-annotator icon intent-annotator

Simple tool to add new intent examples to IBM's Watson Assistant workspace json

kube-shell icon kube-shell

Kubernetes shell: An integrated shell for working with the Kubernetes

maml icon maml

Code for "Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks"

mlflow icon mlflow

MLflow Docker images and methods to deploy to different environments

mnist icon mnist

Tutorial on how to create (from scratch) a neural network that can recognize hand-written digits

multilevel-glm-in-python icon multilevel-glm-in-python

Collection of scripts that show different possibilities how to fit multilevel generalized linear models in Python.

pair-test icon pair-test

Exercise in various methods how to perform pairwise test for equality of expected values

send-to-slack icon send-to-slack

Set of utility functions for sending files and plots from python directly to slack

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