If you’ve ever spent valuable billable hours time thinking about an algorithm to seek out the optimal cheeseburger, and calculate metrics like the maximal meat-to-bun ratio, then this presentation by noted data scientist Hilary Mason at the Ignite NYC event last year is for you. Hilary, a self-admitted cheeseburger lover, found some data sets in […]
This instructional video explores how to use Hadoop and the Hortonworks Data Platform to analyze sentiment data to understand how the public feels about a product launch – highlighted is the release of the film “Iron Man 3.”
Bits are bits. Whether you are searching for whales in audio clips or trying to predict hospitalization rates based on insurance claims, the process is the same: clean the data, generate features, build a model, and iterate.
In this edition of insideBIGDATA’s Data Science 101 series, I’m going to offer up a short instructional video describing the use of the popular unsupervised learning algorithm, k-means clustering.
“As InfiniBand is getting used in scientific computing environments, there is a big demand to harness its benefits for enterprise environments for handling big data and analytics. This talk will focus on high-performance and scalable designs of Hadoop using native RDMA support of InfiniBand and RoCE. Designs for various components in Hadoop (such as HDFS, MapReduce, RPC, and HBASE) and their benefits based on the RDMA package for Apache Hadoop will be presented. RDMA-based design for scalable Memcached (used in Web 2.0) and the associated benefits will be presented.”
Experfy, based at the Harvard Innovation Lab, announced that it has launched a paradigm-changing, online marketplace that will allow industry leaders to solve their Big Data talent needs. Enterprises now have a central platform for on-demand hiring of vetted experts with algorithmic skills and domain knowledge, primarily for short-term projects related to data, analytics and business intelligence.
In this video from GTC 2014, Todd Mostak from MapD demonstrates the company’s GPU-powered in-memory relational database software for Big Data. The Cambridge, Mass., based startup has built a high-speed GPU in-memory database that brings interactivity to big data. It can, for example, track more than a billion tweets worldwide at a time – and provide real-time visual analysis of the data. MapD was also announced as the winner of the GPU Technology Conference’s Early Stage Challenge this year, and they will be coming home with a cool $100,000 check.