# First post

Ah, the classical “first post”, often the only post in the blog. Let us hope this is not the case.

I feel like I should write down some things about my side projects. I tried using Medium, but it has two significant problems: the platform feels too monetized, and it really doesn’t work very well together with LaTeX. Since I like to think a lot in mathematical terms, having good LaTeX support is just essential.

This website is made using Jekyll and hosted on github-pages. I don’t know how good this is, but we shall see. At least like it better.

I hope to shortly make a couple posts about recent projects:

• Bayesian analysis of exam grades (I posted this over on Github, but since then I have done significant work on the subject)
• Analysis of moodle-logs
• Analysis of my last.fm scrobble history
• Analysis of ISU figure skating scores, and proving statistically the fact that judging is biased.
• How to scrape data from pdf files (using the ISU scores as example)

## My thesis in a nutshell

Read this blog post if you’re curious what I worked on during my PhD!

## GMRES: or how to do fast linear algebra

Linear least-squares system pop up everywhere, and there are many fast way to solve them. We’ll be looking at one such way: GMRES.

## Machine learning with discretized functions and tensors

We recently made a paper about supervised machine learning using tensors, here’s the gist of how this works.

## Low-rank matrices: using structure to recover missing data

A lot of data is naturally of ‘low rank’. I will explain what this means, and how to exploit this fact.

## How to edit Microsoft Word documents in Python

Parsing and editing Word documents automatically can be extremely useful, but doing it in Python is not that straightforward.

## Blind deconvolution #4: Blind deconvolution

Finally, let’s look at how we can automatically sharpen images, without knowing how they were blurred in the first place.