The MathWorld article on Gelfand’s question says that the answer is no for values of n less than 100,000. That range seemed small to me. My intuition was that you’d need to try larger values of n to have a reasonable chance of finding a solution.
Jan Aasman of Franz and Matthieu Jonglez of Smartlogic explore the meaning, theory, and manifold purposes of Content Intelligence and Graph Search, including an in-depth enterprise use case.
Today Apache Lucene and Solr PMC announced another version of Apache Lucene library and Apache Solr search server numbred 4.3.1
Big Data is a fast growing trend in enterprise applications that comes with a novel promise compare to past technological revolutions . . .
Here's a little r-script to convenientely download high quality digital elevation data, i.e. for the Alps, from HERE . . .
After opening up our new Boston office earlier this year (for any of you locals we’re down in the innovation district on Summer St) we finally got the chance to attend out first AWS Boston meetup.
Presto is an ANSI-SQL compatible real-time data warehouse query engine so existing data tools should be working with it unlike Hive which needed special integration.
The commands I came across with, while working with svn in Linux.
Technology is allowing us to harness big data and understand it in milliseconds but will this quest for speed be your ultimate undoing?
Helen Bravo, of the Open Web Application Security Project, presents a 35-minute discussion at Snowfroc 2013.
A friend at work, Drew Fustin, proposed this puzzle in our group chat one day as I was meandering on about Bayesian shiny things.
John A. De Goes, CTO of Precog, discusses PrecogDB -- a data science platform in Scala.
As a data engineer and scientist, I have been following the NSA PRISM raw intelligence mining program with great interest. The engineering complexity, breadth and scale is simply amazing compared to say credit card analytics (Fair Issac) or marketing analytics firms like Acxiom.
We recently uploaded a revised version of our work, with Ewen Gallic on Visualizing spatial processes using Ripley’s correction: an application to bodily-injury car accident location.
Monica Rogati, Senior Data Scientist at LinkedIn, discusses data science and predictive modeling.
In the real-world, we can find so many objects around us, for example Cars, Birds, Humans etc. All these objects have a state and behavior. If we consider a Car then it have some data speed, lights on, direction, etc. and have some actions turn right, accelerate, turn lights on, etc.
BPM is established, tools are stable, many companies use it successfully. However, today’s business processes are based on data from relational databases or web services.
Spring XD makes it easy to solve common big data problems such as data ingestion and export, real-time analytics, and batch workflow orchestration.
The development team moved their persistence layer from Oracle to Cassandra. How does the Data Warehouse team extract data for reporting?
Suppose you have a large n × n grid of lights, some turned on and some turned off. Along the side of each row is a switch that can toggle the lights in that row, turning on lights that were originally off and vice versa. There are similar switches along the top that can toggle the lights in each column. How many lights can you turn on?
This fifteen minute video from Troy Sadkowsky explores how data scientists approach problem-solving -- starting with recognizing your problem for what it is.
We encountered an issue with one of our clients when the SOA Purge wasn’t being very effective due to the running mediator instances even though the rest of the flow trace had completed, This wasn’t an issue for business as such however in most cases caused them to fall out of the criteria for Purge due to the state in which these mediator instances were in.
If you compute the standard deviation of a data set by directly implementing the definition, you’ll need to pass through the data twice: once to find the mean, then a second time to accumulate the squared differences from the mean.
Graph analysis and big data are overlapping areas and then I came across this piece of text which beautifully summarizes the difficulty of discovering the unknown.