k-Nearest neighbors

KNN is simple. I’m interested in trying it because it seems like the way some traders think. In interesting situations, they think back to other stocks that were in a similar situation in the past and bet on a similar outcome. The trick is knowing what aspects of a situation are really useful for prediction.

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Poor man’s cluster

This part might just be me cargo-culting, but I feel like every research operation needs a compute cluster. Any self-respecting quant should be able expand their computational needs to fill an arbitrarily large number of servers. The cluster I’ve just built is a low-budget clunker, made of a motley bunch of leftover and refurbished servers, linked together with parts off eBay. But I’m very proud of it!

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Reviews of distributed filesystems

I have a lot of data to work with, and I want to do it with just my mismatched bunch of servers, desktops, SSDs, and spinning disks. My equipment is old, so I want a filesystem that is robust not only to the failure of any drive, but also to the failure of any one machine. My preference is to build a hyper-converged system, where each machine hosts data in addition to working on compute jobs. Following are reviews I found on the main open-source distributed filesystems out there:

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Securing a research VLAN on a retail router with DD-WRT

I’m building a lean research operation, and I don’t really have need of a high-end firewall, along with the associated licensing costs. So, I’ve decided to try firmware-modding a retail router. I’m hoping it will be an inexpensive way to increase security and get a few more features than a typical WiFi router.

After a bit of reading, I settled on the Netgear Nighthawk R7000, partly because it was in stock at Walmart. Right on the box, it promotes a firmware-modding website run by Netgear. It is compatible with DD-WRT, which has some nice features.

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