production

XGBoost is a fantastic open source implementation of Gradient Boosting Machines, a general purpose supervised learning method that achieves the highest accuracy on a wide range of datasets in practical applications. Deep learning is all the hype now, but apart from specific domains such as images, speech or text (i.e. problems with higher-level abstractions to be learnt and/or perception problems, where deep learning achieved some remarkable results indeed), it is usually outperformed by Gradient Boosting in a majority of general business domains and supervised learning applications. Proof of this and also because XGBoost has an easy-to-use interface from both R and Python, XGBoost has become a favorite tool in Kaggle competitions. Besides feature engineering, cross-validation and ensembling, XGBoost is a key ingredient for achieving the highest accuracy in many data science competitions and more importantly in practical applications.

Shiny takes inputs from UI elements and sends them to the server, where the application can access them as R variables. While Shiny has security measures in place, as in any typical web application, it remains the developer’s responsibility to sanitize the inputs before using them. For example, Shiny has no way to protect you if you are using an input in a SQL query such as select ... from ... where field = 'input'. Someone manipulating the websocket communication can craft a specially-formatted input that can force the database to execute a query that it is not supposed to do, termed an SQL injection. This might give an attacker access to private data or the ability to do other nefarious things, and it is a common security issue.

Last week the LA R meetup featured another round of 5 speakers each highlighting a few things they had found interesting at the useR! 2014 conference. This was the second such event after the first one in September - probably because useR! was awesome enough that it inspired 10 volunteers to stand up on stage and talk more about it.

(Please click here if the video above doesn’t load.) The video above is from an event at useR! 2014 consisting of Yasmin Lucero’s presentation plus an incredible panel discussion, which is included here. The title of the panel was “R’s Place in the Production Environment”, and was moderated by Tareef Kawaf, President at RStudio. Five high-profile members of the R community were on this panel, spanning the gamut of the enterprise:

(Please click here if the video above doesn’t load.) During useR! 2014, the LA R Meetup (run by Szilard Pafka) organized an event focused on R’s status in industry. This event took the form of a presentation by Yasmin Lucero, Senior Statistician at AOL-Gravity, followed by a panel discussion. The video above captures the presentation, where Yasmin provides an excellent overview of the current status of R in the enterprise and breaks down the taxonomy of solutions for which R is commonly chosen as a development platform. From batch reporting and dashboards for internal deployment to full blown public facing analytics data products, R has certainly found a home in business. Yasmin’s talk concludes with specific, operational aspects of managing R in the enterprise, such as library and dependency management. Enjoy the video and don’t forget to tune in for Part 2 of this session where the panel discussed “R’s Place in the Production Environment.”