Welcome to my personal blog on topics related to tech and data.
The open source landscape for data science and machine learning is pretty vast and ever-expanding. Here, I am trying to keep track of some of these packages.
Feb 6, 2022
In this article we discuss differences between experimental and observational data and pitfalls in using the latter for data-driven decision-making.
Aug 18, 2021
Increasingly, enterprises embrace decision-making based on data, thus becoming data-driven companies. However, decisions based purely on data can lead to mistakes and may waste resources. Combining causal models with data promises to fix these issues. In this article I explain why the causality-driven company is the sensible step up from the data-driven company.
May 10, 2020
In this article we analyze direct marketing data and prototype a decision model to optimize future marketing uplift.
Jan 12, 2020
In this article we prototype an algorithm that automatically scores engine health based on vehicle CAN bus data.
Jan 5, 2020
In this article we implement multiclass classification on an online stream of documents implemented in Python.
Oct 10, 2014
In this article we use Python and graphs to discover linkages between scientific papers.
Mar 22, 2014
In this article we apply latent dirichlet allocation (LDA) to discover topic clusters in academic papers.
Feb 16, 2014
In this article we implement the well-known finite difference method Crank-Nicolson in combination with a Runge-Kutta solver in Python.
Jan 9, 2014
In this article we adapt numerical solvers for partial differential equations to handle dynamic domain sizes in Python
Jan 8, 2014
In this article we look at document clustering implemented in Python with scikit-learn.
Dec 16, 2013
In this article we implement the well-known finite difference method Crank-Nicolson in Python.
Dec 3, 2013