I wanted to highlight a recent paper I came across, which is also a nice follow-up to my earlier post on pruning neural networks:

As Kaggle’s moderating data scientist for the Data Science Bowl, I’m fortunate to have met first-time competitor Nicole Finnie. Her team (Unet Nuke) impressively ranked within the top 2%, earning Nicole a silver medal. More impressively, I learned that Nicole had no ML/DS experience just a year ago, and picked up these new skills through online classes during her recent maternity leave.

In this installment of the Learn R series, we’re going to start to have a look at data types, dataframes and what on earth you do with them!

Hello Stitch Fix followers, check out where our fellow Stitch Fixers are speaking in the month of May.

We have a new #1 on our leaderboard – a competitor who surprisingly joined the platform just two years ago. Shubin Dai, better known as Bestfitting on Kaggle or Bingo by his friends, is a data scientist and engineering manager living in Changsha, China. He currently leads a company he founded that provides software solutions to banks. Outside of work, and off Kaggle, Dai’s an avid mountain biker and enjoys spending time in nature. Here’s Bestfitting:

A couple weeks ago, I started following the @everytract twitter bot account (by @fitnr), which is tweeting an aerial image of every census tract in America:

In a dank corner of the internet, it is possible to find actresses from Game of Thrones or Harry Potter engaged in all manner of sex acts. Or at least to the world the carnal figures look like those actresses, and the faces in the videos are indeed their own. Everything south of the neck, however, belongs to different women. An artificial intelligence has almost seamlessly stitched the familiar visages into pornographic scenes, one face swapped for another. The genre is one of the cruelest, most invasive forms of identity theft invented in the internet era. At the core of the cruelty is the acuity of the technology: A casual observer can’t easily detect the hoax.

A few days ago while I was bored at the office, I had a chat with a friend about absurd movies. He told me all about Kung Fury. The latter, as he described, was a 30-minute flick that pays homage to all things 80s. With my interest piqued, I googled the film and saw its poster. What greeted me was the following low-budget hack job.

As I have mentioned before, I like running queries directly from R, so I can analyze the results directly. One downside of this is that sometimes there are queries that take a few minutes to finish, so I would be better saving the result and reading it from disk, but if I have to modify anything in the SQL syntax I also have to replace the previous file with the results. That defeats the purpose of running the entire thing from R.

Roger Peng ** 2018/05/03