# Mikkel Hartmann Jensen

I am a 20 something physicists trying to learn machine learning. When I
am faced with a difficult problem I find it usefull to write a text
about it. This is where I keep these texts. They are mostly here so future
Mikkel can find them easily but feel free to read along.

If you want to know more you can check out my
CV or my profiles at:
LinkedIn ,
ORCiD or
Google Scholar .

## Learning Python

Lists and Vectors:
I have been running into trouble while implementing machine learning
algorithms in python -- not because the math is giving me a hard time, but
because I unintentionally mix up the different structures that Python and
the Numpy package provide. In this post I attempt to clear the waters.

## Machine Learning - Reccomender systems

One of my favortie features of Spotify, Steam and Goodreads is the reccomendations
they provide. So I've decided the write a reccomender system for video games.

Collaberative Filtering
- The mathematics: Before writing any code one should first understand the
algorithm and the mathematics behind it. This post is all about the mathematics.

Collaberative Filtering
- Writing it in python: While the level of abstraction mathamatics
providde is great any implementation often raises several issues. In this
post I go through the particular implementation I have written in Python.

Collaberative Filtering
- Testing the model: Once you have a working system it needs to be
tested. This take a lot of work and in many ways this is where it gets
interesting -- how can you tweak the parameter to make it preform better?
Is is baiased in any way? These are the kinds of questions that I address
in this post.