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Weird dataset: identifying sexual predators in chat rooms

To all of the bored data scientists who are looking for interesting demo. (Alternatively, to all the startups who want to do a fraud detection demo). I stumbled upon this weird dataset which was part of PAN 2012 conference: identifying sexual predators in chat rooms.


A less bizarre dataset is the beer classification dataset reported in William M. Briggs blog. It is the classical geeky cool dataset since it shows you are a data scientist who likes beer.

Additional borderline dataset is how clean are SF restaurants dataset I wrote about before.

Yeppp! math library

I got this from my colleague Chris DuBois: Yeppp! is a new math library from Georgia Tech. According to their benchmark page they have impressive performance vs. other packages including intel MKL.  Yeppp! supports C/C++/Java and Fortran interfaces. It is licensed using the creative commons 3 license.

Parquet: efficient column store on Hadoop

I got this from my collaborator Joey Gonzalez. Cloudera is backing up Apache Parquet, an efficient column store on top of Hadoop. Which is an open source version of Google Dremel.

If you like to hear more about Cloudera's vision about new trends data science, you should attend our 3rd GraphLab Conference to hear Josh Wills, director of data science @ Cloudera.

Big data faculty positions at Emory University

I got this from Eugene Agichtein, a Prof. at Emory University:

We are starting a 6-faculty "big data" faculty search, with machine learning and systems being key focus areas. The position ad is here:http://www.mathcs.emory.edu/uploaded-files/Emory-DS-Ad.pdf. We are starting to review candidates soon.

Emory U is in Atlanta, GA, and has been a consistently ranked in the top 20 of U.S. universities, and while traditionally has been focusing on life sciences research, is now seriously expanding computational-* programs across all schools. The CS Phd program was only started in 2007, but has managed to attract pretty good students.

TunkRank on GraphLab

Just learned that students from EPFL have implemented an algorithm called TunkRank on top of GraphLab. An explanation of the algorithm is available here.

The advising researcher is Prof. Mike Ferdman, From Stoney Brook University. This work was done as part of the CloudSuite project.

HP Titan - a notable presentation by Dr. Ira Cohen, HP Software

A great and impressive talk by Ira Cohen, CTO of HP Software at our applied ML meetup yesterday. HP got to the conclusion that they can not hire enough data scientists. So they set an operation where smart programmers are educated to use data science tools. First the programmers undergo a 5 days applied ML course. Then they are supplied with Titan which is basically ML tooset for dummies. Titan have 4 conceptual steps:

1) Data import - connects to data sources like twitter, salesforces, web, database etc

2) Data filter - automatic data filtering and normalization, user selects the interesting target to predict. 

3) Data analytics - the systems suggests automatically which ML methods to use. The user just clicks then ones that fit. (Very high level - like classify, regress etc.).

Once a topic is selected, few algos are run in parallel and the results shown to the user. 

4) Publish - once the user is happy with the results, he can publish in one of several visual forms like graphs, geographical maps etc. The publish creates either an interactive web page or pdf with the results. 

The results are very impressive. around 70 programmers had the ML training. In 4 months they have created around 30 projects which many of them are pushed towards deployment in production.

One case study he gave is customer leads prediction. You simply select data source = salesforce, you select the target (sell/ no sell), the ML method (classify), after a few minutes you an interactive application with zoomable US maps that shows you  sales predictions. Everything is highly visual and appealing.