Jan Ruijgrok
Data Scientist
Data Scientist with math and hacking background. Experience in and passionate about machine learning.
Personal Info
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Date of Birthπ-day
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Phone(+31)655347905
Education
HBO – Big data specialist LOI
2019-2020Microsoft Professional Program for Data Science
2018Applied Mathematics TU Delft
1991-1997
Skills
Machine Learning (Azure Machine Learning Studio) 90%
Math./Statistics 90%
Visualization and Exploration of Data (Excel) 85%
Computer Programming (C#, T-SQL, R, Python) 80%
Agile/Scrum 80%
Work Experience
Ministry of the Interior and the Kingdom Relations
2019-continuePiYan IT
2018-2019Ordina Software Development
2008-2018Ordina Technical Automation
2007-2008LogicaCMG
2000-2007Ministry of the Interior and the Kingdom Relations
1999-2000TNT Post
1997-1998
Library
This blog aims to refer to professional articles.
On Prime Numbers
Solving the Riemann Hypothesis is of great importance because many theorems have been proven under the assumption of this hypothesis. Inspired by Goldbach’s theorem, I introduce a new approach for possible proofs.
Smart Transformations in a Network Intrusion Detection System
In this article I present my analysis of a supervised learning experiment solving a two class classification problem in a network intrusion detection system. The goal of the experiment is to study smart transformations on some continuous variables on the train dataset.
K-Means Clustering at Work
In this article I present my analysis of an unsupervised learning experiment on a complex dataset that contains clusters. The goal of the experiment is to compute the cluster model using the k-means clustering algorithm.