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Date: Tuesday, Aug 27, 2013
Time: 9AM – 10AM PT (Click here to see the webinar time in multiple time zones)
Presenter: Mario Inchiosa, Revolution Analytics
Register Now FREE – Only asks for basic contact info.

Hadoop is rapidly being adopted as a major platform for storing and managing massive amounts of data, and for computing descriptive and query types of analytics on that data. However, it has a reputation for not being a suitable environment for high performance complex iterative algorithms such as logistic regression, generalized linear models, and decision trees.

At Revolution Analytics, we think that reputation is unjustified, and in this webinar, you will learn the approach we have taken to porting our suite of High Performance Analytics algorithms to run natively and efficiently in Hadoop. Our algorithms are written in C++ and R, and are based on a platform that automatically and efficiently parallelizes a broad class of algorithms called Parallel External Memory Algorithms (PEMA’s). This platform abstracts both the inter-process communication layer and the data source layer, so that the algorithms can work in almost any environment in which messages can be passed among processes and with almost any data source.

About the Speaker

Mario Inchiosa Mario Inchiosa’s passion for data science and high performance computing drives his work at Revolution Analytics, where he focuses on delivering parallelized, scalable advanced analytics integrated with the R language. Previously, Mario served as Analytics Architect in IBM’s Big Data organization, working on Social and Machine Data analytics for the BigInsights Hadoop platform. Prior to that, he was US Chief Scientist in Netezza Labs, bringing advanced analytics and R integration to Netezza’s SQL-based data warehouse appliances. Their success led to Netezza’s acquisition by IBM. Mario also served as US Chief Science Officer at NuTech Solutions, a computer science consultancy specializing in simulation, optimization, and data mining, and Senior Scientist at BiosGroup, a complexity science spin-off of the Santa Fe Institute.Dr. Inchiosa holds Bachelors, Masters, and PhD degrees from Harvard University. He has been awarded four patents and has published over 30 research papers, earning Publication of the Year and Open Literature Publication Excellence awards.


Also See:


  1. R vs Python Speed Comparison for Bootstrapping
  2. Step by step to build my first R Hadoop System
  3. What are the hottest areas for CS Research? (Based on Google Research 2013)
  4. Fitting a Model by Maximum Likelihood
  5. “[” and “[[” with the apply() functions
  6. Big Data Sets you can use with R
  7. Rcmdr version 2.0-0 now on CRAN
  8. Select operations on R data frames
  9. Creating a Quick Report with knitr, xtable, R Markdown, Pandoc (and some OpenBLAS Benchmark Results)
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Blog Publisher / Head of Data Science Search

Founder & Head of Data Science Search at Starbridge Partners, LLC.