Louis Meyer

Here are some articles I wrote. I wrote them for myself, as I find these subjects interesting. They also tend to come up in interviews for ML / quant positions, so now I can access my notes online from my phone, while waiting for my interviews at the onsites.

Feel free to send me an email if you believe I made a mistake or have omitted any important details.

These notes are made to be easily readable. It assumes that the reader is familiar with the basic subjects as I rarely explain the terminology or the motivation. I try to make these posts as practical as possible and as information-dense as possible, while introducing concepts intuitively.

Most of the content is generally coming directly from (no more than) a handful of sources, which I do not hesitate to paraphrase from if I like the wording. Even though this is the case, I try to bring a new flavour, add explanations or proofs to the concepts I explore.


Dependency and Discrepancy Measures in RKHS
This one was not meant to be easily readable
Clustering
K-means and Hierarchical Clustering. Distance functions, linkage criterias and model assessment. Also Mixture Models and the EM Algorithm.
The Sharpe Ratio
Pain and Gain. Not for crypto traders, they seem to only get one at the time.
Regularization in Regression
Ridge, Lasso and Elastic-Net: the 3 musketeers. (I actually only use bi-directional LSTMs)
Ordinary Least Squares
A (not so?) gentle introduction to OLS
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