Imagine your company five to ten years down the road: what does it look like? Do you see a well-run organization operating smoothly and proactively? Or is it a more hectic, reactive environment where fires are constantly put out? Maybe you see yourself relaxing on a beach, now that you’ve sold the company? While the
This term, I'm teaching Complex Systems 530 - Computer Modeling for Complex Systems at the University of Michigan Center for the Study of Complex Systems. In the spirit of open science, all course material will be available online at Github. You can browse the repository here: https://github.com/mjbommar/cscs-530-w2015. In the course, we're exploring why and
One of the more exciting and public projects we've been working on lately has finally come to light - our Supreme Court prediction project with Dan Katz and Josh Blackman. This project is exactly what you'd expect - a framework for predicting the Supreme Court, though meant to span the Court's entire history, unlike previous projects.
In our last post, we went over a range of options to perform approximate sentence matching in Python, an import task for many natural language processing and machine learning tasks. To begin, we defined terms like: tokens: a word, number, or other "discrete" unit of text. stems: words that have had their "inflected" pieces removed based on
Let's imagine you have a sentence of interest. You'd like to find all occurrences of this sentence within a corpus of text. How would you go about this? The most obvious answer is to look for exact matches of the sentence. You'd search through every sentence of your corpus, checking to see if every character of the
Isotonic regression is a great tool to keep in your repertoire; it's like weighted least-squares with a monotonicity constraint. Why is this so useful, you ask? Take a look at the example relationship below. (You can follow along with the Python code here). Let's imagine that the true relationship between x and y is characterized piece-wise by a sharp
Thanks to Sam Arbesman (@arbesman) for featuring Dan and my paper, Measuring the Complexity of the Law: The United States Code, on his excellent Wired Science blog, the Social Dimension. You can read the article here, and, as a reminder, all of the code and data from the paper is available in this github repository. Abstact
Do you contract for IaaS, PaaS, or SaaS services like Amazon Web Services or SalesForce? Do you provide SaaS services like “cloud-based applications” or “web applications?” What state are you headquartered in? What states are your servers located in? What states are your customers in, even if for just a moment? Depending on your answer to the
While many Amazon Web Services resources with "state" have CloudWatch sensors available, AWS VPCs and tunnels unfortunately do not. If you're ever in need of a solution to monitor and log the status of VPC tunnels back to another data center or office, my gist below will be right up your alley. It uses
Oracle ORION is a powerful tool for evaluating realistic OLTP and DSS/DW I/O performance. ORION should be a part of every Oracle professional's toolkit for build QA and performance tuning. I've previously used it on this blog to show the performance of Amazon's hi1.4lxarge SSD-backed instances and newer hs1.8xlarge instances with 117GB of RAM and 48TB of
