Mining USPTO full text patent data - Analysis of machine learning and AI related patents granted in 2017 so far - Part 1

The United States Patent and Trademark office (USPTO) provides immense amounts of data (the data I used are in the form of XML files). After coming across these datasets, I thought that it would be a good idea to explore where and how my areas of interest fall into the intellectual property space; my areas of interest being machine learning (ML), data science, and artificial intelligence (AI).

Tired of doing real math 2 — grad school and coffee consumption

Lately I notice a sharp increase in my coffee consumption (reading Howard Schultz’s Starbucks book, which is actually quite good by the way, does not help either ). Having recently transitioned into a new PhD program I started wondering whether my increased coffee consumption has something to do with my higher stress levels in the last few weeks, and how that conjecture generalizes to the rest of my grad school experience. To answer that question I decided to take a look at how much money I have spent at coffee houses over the last few years. …Also, I’m right now over-caffeinated at 1:40am and I have nothing better to do anyway.

Visualization of MRI data in R

Lately I was getting a little bored with genomic data (and then TCGA2STAT started to give me a segfault on my university’s high performance computing facility too ). So I decided to analyze some brain imaging data that I had lying around instead. The first step is to do some visual data exploration. In this blog post I present some functions which I was able to find for MRI visualization in R, and which I found to be very useful. All functions presented below presuppose an image in the NIfTI data format as input, and are very user-friendly.

I had some fun analysing the shelter animal data from kaggle using the Ruby gems daru for data wrangling and statsample-glm for model fitting. In this blog post, I want to demonstrate that data wrangling and statistical modeling is not an area of absolute predominance of Python and R, but that it is possible in Ruby too (though, currently to a much lesser extent).