learning – Page 11 – DECISION STATS

Protected: Benchmarking GNU R: DirkE's view and a Ninja wishlist

Mapreduce Book

Here is a new book on learning MapReduce and it has a free downloadable version as well.

Data-Intensive Text Processing with MapReduce

Jimmy Lin and Chris Dyer

ABSTRACT

Our world is being revolutionized by data-driven methods: access to large amounts of data has generated new insights and opened exciting new opportunities in commerce, science, and computing applications. Processing the enormous quantities of data necessary for these advances requires large clusters, making distributed computing paradigms more crucial than ever. MapReduce is a programming model for expressing distributed computations on massive datasets and an execution framework for large-scale data processing on clusters of commodity servers. The programming model provides an easy-to-understand abstraction for designing scalable algorithms, while the execution framework transparently handles many system-level details, ranging from scheduling to synchronization to fault tolerance. This book focuses on MapReduce algorithm design, with an emphasis on text processing algorithms common in natural language processing, information retrieval, and machine learning. We introduce the notion of MapReduce design patterns, which represent general reusable solutions to commonly occurring problems across a variety of problem domains. This book not only intends to help the reader “think in MapReduce”, but also discusses limitations of the programming model as well.

You can download the book here

This book is part of the Morgan & Claypool Synthesis Lectures on Human Language Technologies. If you’re at a university, your institution may already subscribe to the series, in which case you can access the electronic version directly without cost (see this page for a list of institutional subscribers). Otherwise, to purchase:

Electronic and print copies from Morgan & Claypool (publisher’s site)

Print copies from Amazon.com

Quite explicitly, this book focuses on MapReduce algorithm design, not Hadoop programming. Tom White’s Hadoop: The Definitive Guide is a great resource for learning Hadoop.

Want to be notified of updates? Interested in MapReduce algorithm design? Follow @lintool on Twitter here!

Protected: SAS Institute lawsuit against WPS Episode 2 The Clone Wars

Both Rattle and R Commander are very good GUI’s (graphical user interface) for R, and considerably easier for a beginner than the command line console ( but I am more partial to RCmdr for normal statistical analysis while Rattle seemed to have better Data Mining Interfaces and functionality).

Here is a snapshot for both of them.

Installing them both is a breeze as you set a CRAN Mirror from Normal R Console and install package from list of package names . R has hundreds of packages (All free!!) and you can thus install specific packages to your need and usage.The software R automatically downloads and installs them.

Installling both these GUI will ensure you cut down the time to learn commands as you can first click and try and learn the syntax that is auto generated side by side.

Learning R Easily :Two GUI's

Here is a snapshot for both of them.

Installling both these GUI will ensure you cut down the time to learn commands as you can first click and try and learn the syntax that is auto generated side by side.