http://git-wip-us.apache.org/repos/asf/mahout/blob/ec5eb314/website-old/oldsite/general/books-tutorials-and-talks.md ---------------------------------------------------------------------- diff --git a/website-old/oldsite/general/books-tutorials-and-talks.md b/website-old/oldsite/general/books-tutorials-and-talks.md new file mode 100644 index 0000000..bbbdeef --- /dev/null +++ b/website-old/oldsite/general/books-tutorials-and-talks.md @@ -0,0 +1,121 @@ +--- +layout: default +title: Books Tutorials and Talks +theme: + name: retro-mahout +--- +# Intro + +This page is a place for info about talks (past and upcoming), tutorials, articles, books, slides, PDFs, discussions, etc. about Mahout. No endorsements are implied or +given. + +# Books + +## Mahout specific + + * <a href="http://www.weatheringthroughtechdays.com/2016/02/mahout-samsara-book-is-out.html";>Apache Mahout: Beyond MapReduce</a> by Dmitriy Lyubimov and Andrew Palumbo published Feb 2016. Covers new features in Mahout "Samsara" releases (0.10, 0.11+). + * <a href="http://www.packtpub.com/apache-mahout-cookbook/book";>Apache Mahout cookbook</a>- Book by Piero Giacomelli published Dec 2013 by Packtpub. + * <a href="http://www.manning.com/owen/";>Mahout in Action</a> - Book by Sean Owen, Robin Anil, Ted Dunning and Ellen Friedman published Oct 2011 by Manning Publications. + * <a href="http://www.manning.com/ingersoll/";>Taming Text</a> - By Grant Ingersoll and Tom Morton, published by Manning Publications. Will have some Mahout coverage, but by no means as complete as Mahout in Action. + +## Engineering oriented machine learning books + + * <a href="http://www.amazon.com/Collective-Intelligence-Action-Satnam-Alag/dp/1933988312/ref=pd_bbs_sr_3?ie=UTF8&s=books&qid=1214545249&sr=1-3";>Collective Intelligence in Action</a> + * <a href="http://www.amazon.com/Programming-Collective-Intelligence-Building-Applications/dp/0596529325/ref=pd_bbs_sr_1/104-1017533-9408723?ie=UTF8&s=books&qid=1214593516&sr=1-1";>Programming Collective Intelligence</a> + * <a href="http://www.amazon.com/Algorithms-Intelligent-Web-Haralambos-Marmanis/dp/1933988665/ref=sr_1_1?s=books&ie=UTF8&qid=1298005918&sr=1-1";>Algorithms of the Intelligent Web</a> + +## Scientific background + + * <a href="http://www.cs.waikato.ac.nz/~ml/weka/book.html";>Data Mining: Practical Machine Learning Tools and Techniques</a> + * <a href="http://www-nlp.stanford.edu/IR-book/";>Introduction to Information Retrieval</a> + * <a href="http://www.amazon.com/Machine-Learning-Mcgraw-Hill-International-Edit/dp/0071154671/ref=pd_bbs_sr_1?ie=UTF8&s=books&qid=1214593709&sr=8-1";>Machine Learning</a> + * <a href="http://www.amazon.com/Pattern-Recognition-Learning-Information-Statistics/dp/0387310738/ref=pd_bbs_sr_2?ie=UTF8&s=books&qid=1214593709&sr=8-2";>Pattern Recognition and Machine Learning (Information Science and Statistics) </a> + +# News, Articles and Tutorials + + * [Mahout 0.10.x: first Mahout release as a programming environment](http://www.weatheringthroughtechdays.com/2015/04/mahout-010x-first-mahout-release-as.html) + * [Comparing Document Classification Functions of Lucene and Mahout](http://soleami.com/blog/comparing-document-classification-functions-of-lucene-and-mahout.html) + * <a href="http://www.ibm.com/developerworks/java/library/j-mahout-scaling/";>Apache Mahout: Scalable Machine Learning for Everyone</a> + * <a href="http://emmaespina.wordpress.com/2011/04/26/ham-spam-and-elephants-or-how-to-build-a-spam-filter-server-with-mahout/";>How to build a spam filter server with Mahout</a> - Applying classification on a live server - April 2011 + * <a href="http://ssc.io/deploying-a-massively-scalable-recommender-system-with-apache-mahout/";>Deploying a massively scalable recommender system with Apache Mahout</a> - Blogpost of Sebastian Schelter in April 2011 + * <a href="http://www.redmonk.com/cote/2010/11/04/makeall013/";>Apache Mahout & the commoditization of machine learning </a> - Podcast interview with Grant Ingersoll at ApacheCon 2010 + * <a href="http://isabel-drost.de/hadoop/slides/devoxx.pdf";>Apache Mahout 0.4 mit neuen Algorithmen</a> - published after the 0.4 release by heise Open/ Developer, November 2010 + * <a href="http://www.infoq.com/news/2009/04/mahout";>Mahout on InfoQ</a> - Interview with Grant Ingersoll on InfoQ + * <a href="http://www.cloudera.com/blog/2009/04/21/hadoop-uk-user-group-meeting/";>Mahout in the Cloudera weblog</a> - published after the Hadoop user group UK. + * <a href="http://blog.athico.com/2008/08/machine-learning-and-apache-mahout.html";>Mahout in the Drools weblog</a> - Michael Neale published an article on Mahout in the drools weblog + * <a href="https://www.ibm.com/developerworks/java/library/j-mahout/index.html";>Introducing Apache Mahout</a> - Grant Ingersoll - Intro to Apache Mahout focused on clustering, classification and collaborative filtering. Japanese translation available at: [http://www.ibm.com/developerworks/jp/java/library/j-mahout/](http://www.ibm.com/developerworks/jp/java/library/j-mahout/) + * <a href="http://philippeadjiman.com/blog/2009/11/11/flexible-collaborative-filtering-in-java-with-mahout-taste/";>Flexible Collaborative Filtering In Java With Mahout Taste</a> - Philippe Adjiman - Quick starting guide on how to use the collaborative filtering package of Mahout (called Taste) to quickly and flexibly create, test and compare tailored recommendation engines. + * <a href="http://www.lucidimagination.com/blog/2010/03/16/integrating-apache-mahout-with-apache-lucene-and-solr-part-i-of-3/";>Integrating Mahout with Lucene and Solr</a> Three part series on ways to integrate Mahout with Lucene and Solr + * <a href="https://www.youtube.com/watch?v=yD40rVKUwPI";>Mahout Item Recommender Tutorial using Java and Eclipse</a> - YouTube video tutorial by Steve Cook + + +# Coursework/Lectures + + * <a href="http://videolectures.net/mlss05us_chicago/";>http://videolectures.net/mlss05us_chicago/</a> + * <a href="http://videolectures.net/mlas06_pittsburgh/";>http://videolectures.net/mlas06_pittsburgh/</a> + * <a href="http://see.stanford.edu/see/lecturelist.aspx?coll=348ca38a-3a6d-4052-937d-cb017338d7b1";>Stanford Lectures on Machine Learning by Andrew Ng</a> + * <a href="https://docs.google.com/open?id=0ByhGL2_SCeitMDQ3OTczNjItM2ZjYi00ZDg5LWE0MzItZGQxODQ5NzkzYjNj";>CMU@Qatar Introduction to Mahout lecture</a> + + +# Talks + +In reverse chronological order, so that most recent talks are at the top + + * [Distributed Machine Learning with Apache Mahout] Suneel Marthi at Apache Big Data North America, Vancouver, Canada, May 11, 2016 and MapR Washington DC Big Data Everywhere, Tysons, VA, June 2 2016 + * [Declarative Machine Learning with the Samsara DSL](http://www.slideshare.net/FlinkForward/sebastian-schelter-distributed-machine-learing-with-the-samsara-dsl) Sebastian Schelter at Flink Forward Conference, Berlin Germany, October 2015. + * [Bringing Algebraic Semantics to Mahout](http://www.slideshare.net/sscdotopen/bringing-algebraic-semantics-to-mahout) Sebastian Schelter at HPI Infolunch, Potsdam Germany, May 2014 + * Mahout Spark and Scala bindings: Bringing Algebraic Semantics ([slides](http://www.slideshare.net/DmitriyLyubimov/mahout-scala-and-spark-bindings)/[video](http://youtu.be/h9dpmvNW1Dw)) - Dmitriy Lyubimov at Mahout Meetup, April 17, 2014. + * Mahout Future Directions - Ted Dunning, Suneel Marthi, Sebastian Schelter at Hadoop Summit Europe 2014, Amsterdam, April 3, 2014 + * Building Recommender Systems for Mere-Mortals - Sebastian Schelter at Researchgate Developer Day, Berlin, November 2013 + * Recommendations with Apache Mahout - Sebastian Schelter at IBM Almaden Research Center, San Jose, September 2013 + * <a href="http://de.slideshare.net/sscdotopen/next-directions-in-mahouts-recommenders";>Next Directions in Mahoutâs Recommenders</a> - Sebastian Schelter at Bay Area Mahout Meetup, Redwood City, August 2013 + * <a href="http://de.slideshare.net/sscdotopen/new-directions-in-mahouts-recommenders";>New Directions in Mahoutâs Recommenders</a> - Sebastian Schelter at Recommender Systems Get Together Berlin, April 2013 + * <a href="http://www.slideshare.net/VaradMeru/introduction-to-mahout-and-machine-learning";>Introduction to Mahout and Machine Learning</a> - Slides by Varad Meru, Software Development Engineer at Orzota. July 27th, 2013. + * <a href="http://de.slideshare.net/sscdotopen/introduction-to-collaborative-filtering-with-apache-mahout";>An Introduction to Collaborative Filtering with Apache Mahout</a> - Sebastian Schelter at Recommender Systems Challenge Workshop in conjunction with ACM RecSys 2012, Dublin, September 2012 + * <a href="https://github.com/ManuelB/facebook-recommender-demo/raw/master/docs/Talk-BedCon-Berlin-2012.pdf";>How to build a recommender system based on Mahout and JavaEE</a> - Slides by Manuel Blechschmidt at Berlin Expert Days March, 2012. + * <a href="http://lanyrd.com/2011/apachecon-north-america/skdtb/";>Apache Mahout for intelligent data analysis</a> - Slides from Isabel Drost at Apache Con NA November, 2011. + * <a href="http://lanyrd.com/2011/apachecon-north-america/skdrk/";>Dr. Mahout: Analyzing clinical data using scalable and distributed computing</a> - Slides from Shannon Quinn at Apache Con NA November, 2011. + * Frank Scholten at Berlin Buzzwords on June 7, 2011. + * Introduction to Collaborative Filtering using Mahout (updated) - Talk by Sean Owen at the London Hadoop User Group on April 14, 2011. + * <a href="http://www.meetup.com/LA-HUG/pages/Video_from_March_16th_LA-HUG_Ted_Dunning_Mahout";>Cool Tricks with Classifiers</a> - Talk by Ted Dunning at the Los Angeles HUG talking about Mahout classifiers on March 16, 2011. + * First Mahout Hackathon, Berlin, March 2011 + * <a href="http://blog.jteam.nl/2011/01/13/announcement-lucene-nl-mahout-meetup-with-isabel-drost-feb-7/";>Mahout meetup</a> - there were two talks at the Apache Mahout meetup at JTeam in Amsterdam, February 2011. <a href="http://isabel-drost.de/hadoop/slides/jteam.pdf";>intro slides</a> + * <a href="http://www.fosdem.org/2011/schedule/event/mahoutclustering.html";>Mahout clustering </a> - Talk on Mahout clustering at data dev room FOSDEM, February 2011. + * Scaling Data Analysis with Apache Mahout - talk on Mahout at O'Reilly Strata, February 2011. + * <a href="http://www.slideshare.net/jaganadhg/mahout-tutorial-fossmeet-nitc";>Practical Machine Learning</a> - Slides from Biju B and Jaganadh G, FOSSMEET-NITC, Calicut, India, February 2011. + * <a href="http://www.javaedge.com/jedge/pdf/Mahout.pdf";>Mahout at AlphaCSPs The Edge 2010 (pdf)</a> - <a href="http://www.slideshare.net/arikogan/mahouts-presentation-at-alphacsps-the-edge-2010";>slideshare</a> - Slides from <a href="http://il.linkedin.com/in/arielkogan";>Ariel Kogan</a> AlphaCSP's The Edge, December 2010. + * <a href="http://isabel-drost.de/hadoop/slides/devoxx.pdf";>Intelligent data analysis with Apache Mahout</a> - Slides from Isabel Drost, Devoxx Antwerp, November 2010. + * <a href="http://isabel-drost.de/hadoop/slides/codebits.pdf";>Apache Mahout introduction</a> - Slides from Isabel Drost, codebits Lisbon, November 2010. + * <a href="http://isabel-drost.de/hadoop/slides/apachecon_2010.pdf";>Apache Mahout - Making Data Analysis Easy</a> - Slides from Isabel Drost, Apache Con US Atlanta, November 2010. + * <a href="http://www.slideshare.net/jaganadhg/bck9";>Practical Machine Learning</a> - Slides from Jaganadh G, BarCamp Kerala 9, November 2010. + * <a href="http://www.slideshare.net/tdunning/sdforum-11042010";>Mahout and its new classification framework</a> - Slides from Ted Dunning, SDForum, November 2010. + * <a href="http://www.slideshare.net/sscdotopen/mahoutcf";>Distributed Item-based Collaborative Filtering with Apache Mahout</a> - Slides from Sebastian Schelter, Hadoop Get Together Berlin, October 2010. + * <a href="http://isabel-drost.de/hadoop/slides/HMM.pdf";>Hidden Markov Models for Mahout</a> - Slides from Max Heimel, Hadoop Get Together Berlin, October 2010. + * <a href="http://www.slideshare.net/robinanil/oscon-apache-mahout-mammoth-scale-machine-learning";>Apache Mahout Mammoth Scale Machine Learning </a> - Slides from Robin Anil, OSCON 2010. + * <a href="http://slidesha.re/9LxOIu";>Intro to Apache Mahout</a> - Slides from Grant Ingersoll, RTP Semantic Web Group. + * <a href="http://www.slideshare.net/ydn/3-biometric-hadoopsummit2010";>Case study: Biometric Databases and Hadoop </a> - Slides from Jason Trost, Hadoop Summit 2010. + * <a href="http://www.slideshare.net/hadoopusergroup/mail-antispam?from=ss_embed";>Spam Fighting at Yahoo</a> + * <a href="http://www.slideshare.net/hadoopusergroup/bixo-hug-talk?from=ss_embed";>Web Mining with Ken Krugler</a> + * <a href="http://berlinbuzzwords.wikidot.com/local--files/links-to-slides/ingersoll_bbuzz2010.pdf";>Keynote on intelligent search</a> - Slides from Grant Ingersoll, Berlin Buzzwords, June 2010. + * <a href="http://berlinbuzzwords.wikidot.com/local--files/links-to-slides/owen_bbuzz2010.pdf";>Simple co-occurrence-based recommendation on Hadoop</a> - Slides from Sean Owen, Berlin Buzzwords, June, 2010. + * <a href="http://berlinbuzzwords.wikidot.com/local--files/links-to-slides/scholten_bbuzz2010.odp";>Introduction to Collaborative Filtering using Mahout</a> - Slides from Frank Scholten, Berlin Buzzwords, June, 2010. + * <a href="http://lucene.grantingersoll.com/2010/02/16/trijug-intro-to-mahout-slides-and-demo-examples/";>Introduction to Scalable Machine Learning</a> - Slides and demos from Grant Ingersoll, March, 2010. + * Mahout @ India Hadoop Summit - Slides from a 1 hour talk on Mahout at the India Hadoop Summit by Robin Anil, February 2010. + * <a href="http://www.isabel-drost.de/hadoop/slides/opensourceexpo09.pdf";>Mahout in 10 minutes</a> - Slides from a 10 min intro to Mahout at the Map Reduce tutorial by David Zülke at Open Source Expo in Karlsruhe, Isabel Drost, November 2009. + * <a href="http://www.isabel-drost.de/hadoop/slides/apacheconus2009.pdf";>Mahout at Apache Con US </a> - Slides from a talk on "Going from raw data to information" (with Mahout) at Apache Con US in Oakland, Isabel Drost, November 2009. + * <a href="http://www.isabel-drost.de/hadoop/slides/froscon2009.pdf";>Mahout at FrOSCon</a> - Slides from a talk on Mahout at FrOSCon in Sankt Augustin, Isabel Drost, August 2009. + * <a href="http://www.isabel-drost.de/hadoop/slides/dai.pdf";>Mahout at DAI group TU Berlin</a> - Slides from a talk on Mahout at the DAI Laboratories TU Berlin, Isabel Drost, July 2009. + * <a href="http://www.isabel-drost.de/hadoop/slides/ulf.pdf";>Mahout at Machine Learning Group TU Berlin</a> - Slides from a talk on Hadoop with some detour to Mahout at the Machine + * Learning Group of Prof. Dr. Klaus-Robert Müller at TU Berlin, Isabel Drost, June 2009. + * <a href="http://www.isabel-drost.de/hadoop/slides/google.pdf";>Mahout at Google Zürich</a> - Slides from a Google tech-talk on the past, present and future of Mahout, Isabel Drost, May 2009. + * <a href="http://static.last.fm/johan/huguk-20090414/isabel_drost-introducing_apache_mahout.pdf";>Hadoop user group UK</a> - Slides from a talk on April 14, 2009 at the Hadoop User Group UK in London, Isabel Drost, April 2009. + * <a href="http://cwiki.apache.org/confluence/download/attachments/88410/SDForum.pdf";>BI Over Petabytes: Meet Apache Mahout</a> - Slides from a talk by Jeff Eastman on April 21, 2009 at the Bay Area SD Forum Business Intelligence SIG meeting at SAP in Palo Alto, CA. + * Lucene Meetup and Apache Barcamp in Amsterdam, March 2009. + * BarCampRDU - (Raleigh) on Aug. 2, 2008 + * Introducing Mahout: Apache Machine Learning - Committer Grant Ingersoll gave a gentle introduction to Mahout and Machine Learning at ApacheCon in November (3rd through 7th) in New Orleans, USA. + * Mahout: Scaling Machine Learning - Introduction to Mahout and machine learning at FrOSCon in Sankt Augustin/Germany, Isabel Drost, August 2008. (<a href="http://cwiki.apache.org/confluence/download/attachments/88410/froscon.pdf";>slides</a>) + * Mahout: Scalable Machine Learning - An introduction to Mahout and machine learning at the first German Hadoop gathering in newthinking store/ Berlin, Isabel Drost, July 2008. + * Apache Mahout: Industrial Strength Machine Learning - Committer Jeff Eastman gave an introduction to Mahout at Yahoo\!, May 2008 + * <a href="http://people.apache.org/~berndf/openexpode08-lucene-talk.pdf";>Apache Lucene - Mach's wie Google</a> - Bernd Fondermann presented an overview of the Apache Lucene project, + * including Mahout at Open Source Expo 2008 in Karlsruhe, May 2008. + * Apache Mahout: Bringing Machine Learning to Industrial Strength - Committer Isabel Drost gave a Fast Feather introduction the the new project Mahout at Apache Con EU April, 2008 \ No newline at end of file
http://git-wip-us.apache.org/repos/asf/mahout/blob/ec5eb314/website-old/oldsite/general/downloads.md ---------------------------------------------------------------------- diff --git a/website-old/oldsite/general/downloads.md b/website-old/oldsite/general/downloads.md new file mode 100644 index 0000000..0822d19 --- /dev/null +++ b/website-old/oldsite/general/downloads.md @@ -0,0 +1,68 @@ +--- +layout: default +title: Downloads +theme: + name: retro-mahout +--- + +<a name="Downloads-OfficialRelease"></a> +# Official Release +Apache Mahout is an official Apache project and thus available from any of +the Apache mirrors. The latest Mahout release is available for download at: + +* [Download Latest](http://www.apache.org/dyn/closer.cgi/mahout/) +* [Release Archive](http://archive.apache.org/dist/mahout/) + + +# Source code for the current snapshot + +Apache Mahout is mirrored to [Github](https://github.com/apache/mahout). To get all source: + + git clone https://github.com/apache/mahout.git mahout + +# Environment + +Whether you are using Mahout's Shell, running command line jobs or using it as a library to build your own apps +you'll need to setup several environment variables. +Edit your environment in ```~/.bash_profile``` for Mac or ```~/.bashrc``` for many linux distributions. Add the following + + export MAHOUT_HOME=/path/to/mahout + export MAHOUT_LOCAL=true # for running standalone on your dev machine, + # unset MAHOUT_LOCAL for running on a cluster + +If you are running on Spark you will also need $SPARK_HOME + +Make sure to have $JAVA_HOME set also + +# Using Mahout as a Library + +Running any application that uses Mahout will require installing a binary or source version and setting the environment. +Then add the appropriate setting to your pom.xml or build.sbt following the template below. + +If you only need the math part of Mahout: + + <dependency> + <groupId>org.apache.mahout</groupId> + <artifactId>mahout-math</artifactId> + <version>${mahout.version}</version> + </dependency> + +In case you would like to use some of our integration tooling (e.g. for generating vectors from Lucene): + + <dependency> + <groupId>org.apache.mahout</groupId> + <artifactId>mahout-hdfs</artifactId> + <version>${mahout.version}</version> + </dependency> + +In case you are using Ivy, Gradle, Buildr, Grape or SBT you might want to directly head over to the official [Maven Repository search](http://mvnrepository.com/artifact/org.apache.mahout/mahout-core). + + +<a name="Downloads-FutureReleases"></a> +# Future Releases + +Official releases are usually created when the developers feel there are +sufficient changes, improvements and bug fixes to warrant a release. Watch +the <a href="https://mahout.apache.org/general/mailing-lists,-irc-and-archives.html";>Mailing lists</a> + for latest release discussions and check the Github repo. + http://git-wip-us.apache.org/repos/asf/mahout/blob/ec5eb314/website-old/oldsite/general/faq.md ---------------------------------------------------------------------- diff --git a/website-old/oldsite/general/faq.md b/website-old/oldsite/general/faq.md new file mode 100644 index 0000000..8e1e592 --- /dev/null +++ b/website-old/oldsite/general/faq.md @@ -0,0 +1,105 @@ +--- +layout: default +title: FAQ +theme: + name: retro-mahout +--- + +# The Official Mahout FAQ + +*General* + +1. [What is Apache Mahout?](#whatis) +1. [What does the name mean?](#mean) +1. [How is the name pronounced?](#pronounce) +1. [Where can I find the origins of the Mahout project?](#historical) +1. [Where can I download the Mahout logo?](#downloadlogo) +1. [Where can I download Mahout slide presentations?](#presentations) + +*Algorithms* + +1. [What algorithms are implemented in Mahout?](#algos) +1. [What algorithms are missing from Mahout?](#todo) +1. [Do I need Hadoop to run Mahout?](#hadoop) + +*Hadoop specific questions* + +1. [Mahout just won't run in parallel on my dataset. Why?](#split) + + +# *Answers* + + +## General + + +<a name="whatis"></a> +#### What is Apache Mahout? + +Apache Mahout is a suite of machine learning libraries designed to be +scalable and robust + +<a name="mean"></a> +#### What does the name mean? + +The name [Mahout](http://en.wikipedia.org/wiki/Mahout) + was original chosen for it's association with the [Apache Hadoop](http://hadoop.apache.org) + project. A Mahout is a person who drives an elephant (hint: Hadoop's logo +is an elephant). We just wanted a name that complemented Hadoop but we see +our project as a good driver of Hadoop in the sense that we will be using +and testing it. We are not, however, implying that we are controlling +Hadoop's development. + +Prior to coming to the ASF, those of us working on the project plan voted between [Howdah](http://en.wikipedia.org/wiki/Howdah) â the carriage on top of an elephant and Mahout. + +<a name="historical"></a> +#### Where can I find the origins of the Mahout project? + +See [http://ml-site.grantingersoll.com](http://web.archive.org/web/20080101233917/http://ml-site.grantingersoll.com/index.php?title=Main_Page) + for old wiki and mailing list archives (all read-only) + +Mahout was started by <a href="http://web.archive.org/web/20071228055210/http://ml-site.grantingersoll.com/index.php?title=Main_Page"; class="external-link" rel="nofollow">Isabel Drost, Grant Ingersoll and Karl Wettin</a>. It <a href="http://web.archive.org/web/20080201093120/http://lucene.apache.org/#22+January+2008+-+Lucene+PMC+Approves+Mahout+Machine+Learning+Project"; class="external-link" rel="nofollow">started</a> as part of the <a href="http://lucene.apache.org"; class="external-link" rel="nofollow">Lucene</a> project (see the <a href="http://web.archive.org/web/20080102151102/http://ml-site.grantingersoll.com/index.php?title=Incubator_proposal"; class="external-link" rel="nofollow">original proposal</a>) and went on to become a top level project in April of 2010.</p><p style="text-align: left;">The original goal was to implement all 10 algorithms from Andrew Ng's paper "<a href="http://ai.stanford.edu/~ang/papers/nips06-mapreducemulticore.pdf"; class="external-link" rel="nof ollow">Map-Reduce for Machine Learning on Multicore</a>"</p> + +<a name="pronounce"></a> +#### How is the name pronounced? + +There are some disagreements about how to pronounce the name. Webster's has it as muh-hout (as in ["out"](http://dictionary.reference.com/browse/mahout)), but the Sanskrit/Hindi origins pronounce it as "muh-hoot". The second pronunciation suggests a nice pun on the Hebrew word ×××ת meaning "essence or truth". + +<a name="downloadlogo"></a> +#### Where can I download the Mahout logo? + +See [MAHOUT-335](https://issues.apache.org/jira/browse/MAHOUT-335) + + +<a name="presentations"></a> +#### Where can I download Mahout slide presentations? + +The [Books, Tutorials and Talks](https://mahout.apache.org/general/books-tutorials-and-talks.html) + page contains an overview of a wide variety of presentations with links to slides where available. + +## Algorithms + +<a name="algos"></a> +#### What algorithms are implemented in Mahout? + +We are interested in a wide variety of machine learning algorithms. Many of +which are already implemented in Mahout. You can find a list [here](https://mahout.apache.org/users/basics/algorithms.html). + +<a name="todo"></a> +#### What algorithms are missing from Mahout? + +There are many machine learning algorithms that we would like to have in +Mahout. If you have an algorithm or an improvement to an algorithm that you would +like to implement, start a discussion on our [mailing list](https://mahout.apache.org/general/mailing-lists,-irc-and-archives.html). + +<a name="hadoop"></a> +#### Do I need Hadoop to use Mahout? + +There is a number of algorithm implementations that require no Hadoop dependencies whatsoever, consult the [algorithms list](https://mahout.apache.org/users/basics/algorithms.html). In the future, we might provide more algorithm implementations on platforms more suitable for machine learning such as [Apache Spark](http://spark.apache.org) + +## Hadoop specific questions +<a name="split"></a> +#### Mahout just won't run in parallel on my dataset. Why? + +If you are running training on a Hadoop cluster keep in mind that the number of mappers started is governed by the size of the input data and the configured split/block size of your cluster. As a rule of thumb, +anything below 100MB in size won't be split by default. \ No newline at end of file http://git-wip-us.apache.org/repos/asf/mahout/blob/ec5eb314/website-old/oldsite/general/glossary.md ---------------------------------------------------------------------- diff --git a/website-old/oldsite/general/glossary.md b/website-old/oldsite/general/glossary.md new file mode 100644 index 0000000..215cd50 --- /dev/null +++ b/website-old/oldsite/general/glossary.md @@ -0,0 +1,11 @@ +--- +layout: default +title: Glossary +theme: + name: retro-mahout +--- +This is a list of common glossary terms used on both the mailing lists and +around the site. Where possible I have tried to provide a link to more +in-depth explanations from the web + +{children:excerpt=true|style=h4} http://git-wip-us.apache.org/repos/asf/mahout/blob/ec5eb314/website-old/oldsite/general/mahout-benchmarks.md ---------------------------------------------------------------------- diff --git a/website-old/oldsite/general/mahout-benchmarks.md b/website-old/oldsite/general/mahout-benchmarks.md new file mode 100644 index 0000000..7a2c643 --- /dev/null +++ b/website-old/oldsite/general/mahout-benchmarks.md @@ -0,0 +1,153 @@ +--- +layout: default +title: Mahout Benchmarks +theme: + name: retro-mahout +--- + +<a name="MahoutBenchmarks-Introduction"></a> +# Introduction + +Depending on hardware configuration, exact distribution of ratings over users and items YMMV! + +<a name="MahoutBenchmarks-Recommenders"></a> +# Recommenders + +<a name="MahoutBenchmarks-ARuleofThumb"></a> +## A Rule of Thumb + +100M preferences are about the data set size where non-distributed +recommenders will outgrow a normal-sized machine (32-bit, <= 4GB RAM). Your +mileage will vary significantly with the nature of the data. + +<a name="MahoutBenchmarks-Distributedrecommendervs.Wikipedialinks(May272010)"></a> +## Distributed recommender vs. Wikipedia links (May 27 2010) + +From the mailing list: + +I just finished running a set of recommendations based on the Wikipedia +link graph, for book purposes (yeah, it's unconventional). I ran on my +laptop, but it ought to be crudely representative of how it runs in a real +cluster. + +The input is 1058MB as a text file, and contains, 130M article-article +associations, from 5.7M articles to 3.8M distinct articles ("users" and +"items", respectively). I estimate cost based on Amazon's North +American small Linux-based instance pricing of $0.085/hour. I ran on a +dual-core laptop with plenty of RAM, allowing 1GB per worker, so this is +valid. + +In this run, I run recommendations for all 5.7M "users". You can certainly +run for any subset of all users of course. + +Phase 1 (Item ID to item index mapping) +29 minutes CPU time +$0.05 +60MB output + +Phase 2 (Create user vectors) +88 minutes CPU time +$0.13 +Output: 1159MB + +Phase 3 (Count co-occurrence) +77 hours CPU time +$6.54 +Output: 23.6GB + +Phase 4 (Partial multiply prep) +10.5 hours CPU time +$0.90 +Output: 24.6GB + +Phase 5 (Aggregate and recommend) +about 600 hours +about $51.00 +about 10GB +(I estimated these rather than let it run at home for days!) + + +Note that phases 1 and 3 may be run less frequently, and need not be run +every time. But the cost is dominated by the last step, which is most of +the work. I've ignored storage costs. + +This implies a cost of $0.01 (or about 8 instance-minutes) per 1,000 user +recommendations. That's not bad if, say, you want to update recs for you +site's 100,000 daily active users for a dollar. + +There are several levers one could pull internally to sacrifice accuracy +for speed, but it's currently set to pretty normal values. So this is just +one possibility. + +Now that's not terrible, but it is about 8x more computing than would be +needed by a non-distributed implementation *if* you could fit the whole +data set into a very large instance's memory, which is still possible at +this scale but needs a pretty big instance. That's a very apples-to-oranges +comparison of course; different algorithms, entirely different +environments. This is about the amount of overhead I'd expect from +distributing -- interesting to note how non-trivial it is. + +<a name="MahoutBenchmarks-Non-distributedrecommendervs.KDDCupdataset(March2011)"></a> +## Non-distributed recommender vs. KDD Cup data set (March 2011) + +(From the [email protected] mailing list) + +I've been test-driving a simple application of Mahout recommenders (the +non-distributed kind) on Amazon EC2 on the new Yahoo KDD Cup data set +(kddcup.yahoo.com). + +In the spirit of open-source, like I mentioned, I'm committing the extra +code to mahout-examples that can be used to run a Recommender on the input +and output the right format. And, I'd like to publish the rough timings +too. Find all the source in org.apache.mahout.cf.taste.example.kddcup + +<a name="MahoutBenchmarks-Track1"></a> +### Track 1 + +* m2.2xlarge instance, 34.2GB RAM / 4 cores +* Steady state memory consumption: ~19GB +* Computation time: 30 hours (wall clock-time) +* CPU time per user: ~0.43 sec +* Cost on EC2: $34.20 (!) + +(Helpful hint on cost I realized after the fact: you can almost surely get +spot instances for cheaper. The maximum price this sort of instance has +gone for as a spot instance is about $0.60/hour, vs "retail price" of +$1.14/hour.) + +Resulted in an RMSE of 29.5618 (the rating scale is 0-100), which is only +good enough for 29th place at the moment. Not terrible for "out of the box" +performance -- it's just using an item-based recommender with uncentered +cosine similarity. But not really good in absolute terms. A winning +solution is going to try to factor in time, and apply more sophisticated +techniques. The best RMSE so far is about 23. + +<a name="MahoutBenchmarks-Track2"></a> +### Track 2 + +* c1.xlarge instance: 7GB RAM / 8 cores +* Steady state memory consumption: ~3.8GB +* Computation time: 4.1 hours (wall clock-time) +* CPU time per user: ~1.1 sec +* Cost on EC2: $3.20 + +For this I bothered to write a simplistic item-item similarity metric to +take into account the additional info that is available: track, artist, +album, genre. The result was comparatively better: 17.92% error rate, good +enough for 4th place at the moment. + +Of course, the next task is to put this through the actual distributed +processing -- that's really the appropriate solution. + +This shows you can still tackle fairly impressive scale with a +non-distributed solution. These results suggest that the largest instances +available from EC2 would accomodate almost 1 billion ratings in memory. +However at that scale running a user's full recommendations would easily be +measured in seconds, not milliseconds. + +<a name="MahoutBenchmarks-Clustering"></a> +# Clustering + +See [MAHOUT-588](https://issues.apache.org/jira/browse/MAHOUT-588) + + http://git-wip-us.apache.org/repos/asf/mahout/blob/ec5eb314/website-old/oldsite/general/mahout-wiki.md ---------------------------------------------------------------------- diff --git a/website-old/oldsite/general/mahout-wiki.md b/website-old/oldsite/general/mahout-wiki.md new file mode 100644 index 0000000..82edb1c --- /dev/null +++ b/website-old/oldsite/general/mahout-wiki.md @@ -0,0 +1,199 @@ +--- +layout: default +title: Mahout Wiki +theme: + name: retro-mahout +--- +Apache Mahout is a new Apache TLP project to create scalable, machine +learning algorithms under the Apache license. + +{toc:style=disc|minlevel=2} + +<a name="MahoutWiki-General"></a> +## General +[Overview](overview.html) + -- Mahout? What's that supposed to be? + +[Quickstart](quickstart.html) + -- learn how to quickly setup Apache Mahout for your project. + +[FAQ](faq.html) + -- Frequent questions encountered on the mailing lists. + +[Developer Resources](developer-resources.html) + -- overview of the Mahout development infrastructure. + +[How To Contribute](how-to-contribute.html) + -- get involved with the Mahout community. + +[How To Become A Committer](how-to-become-a-committer.html) + -- become a member of the Mahout development community. + +[Hadoop](http://hadoop.apache.org) + -- several of our implementations depend on Hadoop. + +[Machine Learning Open Source Software](http://mloss.org/software/) + -- other projects implementing Open Source Machine Learning libraries. + +[Mahout -- The name, history and its pronunciation](mahoutname.html) + +<a name="MahoutWiki-Community"></a> +## Community + +[Who we are](who-we-are.html) + -- who are the developers behind Apache Mahout? + +[Books, Tutorials, Talks, Articles, News, Background Reading, etc. on Mahout](books-tutorials-and-talks.html) + +[Issue Tracker](issue-tracker.html) + -- see what features people are working on, submit patches and file bugs. + +[Source Code (SVN)](https://svn.apache.org/repos/asf/mahout/) + -- [Fisheye|http://fisheye6.atlassian.com/browse/mahout] + -- download the Mahout source code from svn. + +[Mailing lists and IRC](mailing-lists,-irc-and-archives.html) + -- links to our mailing lists, IRC channel and archived design and +algorithm discussions, maybe your questions was answered there already? + +[Version Control](version-control.html) + -- where we track our code. + +[Powered By Mahout](powered-by-mahout.html) + -- who is using Mahout in production? + +[Professional Support](professional-support.html) + -- who is offering professional support for Mahout? + +[Mahout and Google Summer of Code](gsoc.html) + -- All you need to know about Mahout and GSoC. + + +[Glossary of commonly used terms and abbreviations](glossary.html) + +<a name="MahoutWiki-Installation/Setup"></a> +## Installation/Setup + +[System Requirements](system-requirements.html) + -- what do you need to run Mahout? + +[Quickstart](quickstart.html) + -- get started with Mahout, run the examples and get pointers to further +resources. + +[Downloads](downloads.html) + -- a list of Mahout releases. + +[Download and installation](buildingmahout.html) + -- build Mahout from the sources. + +[Mahout on Amazon's EC2 Service](mahout-on-amazon-ec2.html) + -- run Mahout on Amazon's EC2. + +[Mahout on Amazon's EMR](mahout-on-elastic-mapreduce.html) + -- Run Mahout on Amazon's Elastic Map Reduce + +[Integrating Mahout into an Application](mahoutintegration.html) + -- integrate Mahout's capabilities in your application. + +<a name="MahoutWiki-Examples"></a> +## Examples + +1. [ASF Email Examples](asfemail.html) + -- Examples of recommenders, clustering and classification all using a +public domain collection of 7 million emails. + +<a name="MahoutWiki-ImplementationBackground"></a> +## Implementation Background + +<a name="MahoutWiki-RequirementsandDesign"></a> +### Requirements and Design + +[Matrix and Vector Needs](matrix-and-vector-needs.html) + -- requirements for Mahout vectors. + +[Collection(De-)Serialization](collection(de-)serialization.html) + +<a name="MahoutWiki-CollectionsandAlgorithms"></a> +### Collections and Algorithms + +Learn more about [mahout-collections](mahout-collections.html) +, containers for efficient storage of primitive-type data and open hash +tables. + +Learn more about the [Algorithms](algorithms.html) + discussed and employed by Mahout. + +Learn more about the [Mahout recommender implementation](recommender-documentation.html) +. + +<a name="MahoutWiki-Utilities"></a> +### Utilities + +This section describes tools that might be useful for working with Mahout. + +[Converting Content](converting-content.html) + -- Mahout has some utilities for converting content such as logs to +formats more amenable for consumption by Mahout. +[Creating Vectors](creating-vectors.html) + -- Mahout's algorithms operate on vectors. Learn more on how to generate +these from raw data. +[Viewing Result](viewing-result.html) + -- How to visualize the result of your trained algorithms. + +<a name="MahoutWiki-Data"></a> +### Data + +[Collections](collections.html) + -- To try out and test Mahout's algorithms you need training data. We are +always looking for new training data collections. + +<a name="MahoutWiki-Benchmarks"></a> +### Benchmarks + +[Mahout Benchmarks](mahout-benchmarks.html) + +<a name="MahoutWiki-Committer'sResources"></a> +## Committer's Resources + +* [Testing](testing.html) + -- Information on test plans and ideas for testing + +<a name="MahoutWiki-ProjectResources"></a> +### Project Resources + +* [Dealing with Third Party Dependencies not in Maven](thirdparty-dependencies.html) +* [How To Update The Website](how-to-update-the-website.html) +* [Patch Check List](patch-check-list.html) +* [How To Release](http://cwiki.apache.org/confluence/display/MAHOUT/How+to+release) +* [Release Planning](release-planning.html) +* [Sonar Code Quality Analysis](https://analysis.apache.org/dashboard/index/63921) + +<a name="MahoutWiki-AdditionalResources"></a> +### Additional Resources + +* [Apache Machine Status](http://monitoring.apache.org/status/) + \- Check to see if SVN, other resources are available. +* [Committer's FAQ](http://www.apache.org/dev/committers.html) +* [Apache Dev](http://www.apache.org/dev/) + + +<a name="MahoutWiki-HowToEditThisWiki"></a> +## How To Edit This Wiki + +How to edit this Wiki + +This Wiki is a collaborative site, anyone can contribute and share: + +* Create an account by clicking the "Login" link at the top of any page, +and picking a username and password. +* Edit any page by pressing Edit at the top of the page + +There are some conventions used on the Mahout wiki: + + * {noformat}+*TODO:*+{noformat} (+*TODO:*+ ) is used to denote sections +that definitely need to be cleaned up. + * {noformat}+*Mahout_(version)*+{noformat} (+*Mahout_0.2*+) is used to +draw attention to which version of Mahout a feature was (or will be) added +to Mahout. + http://git-wip-us.apache.org/repos/asf/mahout/blob/ec5eb314/website-old/oldsite/general/mailing-lists,-irc-and-archives.md ---------------------------------------------------------------------- diff --git a/website-old/oldsite/general/mailing-lists,-irc-and-archives.md b/website-old/oldsite/general/mailing-lists,-irc-and-archives.md new file mode 100644 index 0000000..e3862ca --- /dev/null +++ b/website-old/oldsite/general/mailing-lists,-irc-and-archives.md @@ -0,0 +1,75 @@ +--- +layout: default +title: Mailing Lists, IRC and Archives +theme: + name: retro-mahout +--- + +# General + +Communication at Mahout happens primarily online via mailing lists. We have +a user as well as a dev list for discussion. In addition there is a commit +list so we are able to monitor what happens on the wiki and in svn. + +<a name="MailingLists,IRCandArchives-Mailinglists"></a> +# Mailing lists + +<a name="MailingLists,IRCandArchives-MahoutUserList"></a> +## Mahout User List + +This list is for users of Mahout to ask questions, share knowledge, and +discuss issues. Do send mail to this list with usage and configuration +questions and problems. Also, please send questions to this list to verify +your problem before filing issues in JIRA. + +* [Subscribe](mailto:[email protected]) +* [Unsubscribe](mailto:[email protected]) + +<a name="MailingLists,IRCandArchives-MahoutDeveloperList"></a> +## Mahout Developer List + +This is the list where participating developers of the Mahout project meet +and discuss issues concerning Mahout internals, code changes/additions, +etc. Do not send mail to this list with usage questions or configuration +questions and problems. + +Discussion list: + +* [Subscribe](mailto:[email protected]) + -- Do not send mail to this list with usage questions or configuration +questions and problems. +* [Unsubscribe](mailto:[email protected]) + +Commit notifications: + +* [Subscribe](mailto:[email protected]) +* [Unsubscribe](mailto:[email protected]) + +<a name="MailingLists,IRCandArchives-IRC"></a> +# IRC + +Mahout's IRC channel is **#mahout**. It is a logged channel. Please keep in +mind that it is for discussion purposes only and that (pseudo)decisions +should be brought back to the dev@ mailing list or JIRA and other people +who are not on IRC should be given time to respond before any work is +committed. + +<a name="MailingLists,IRCandArchives-Archives"></a> +# Archives + +<a name="MailingLists,IRCandArchives-OfficialApacheArchive"></a> +## Official Apache Archive + +* [http://mail-archives.apache.org/mod_mbox/mahout-dev/](http://mail-archives.apache.org/mod_mbox/mahout-dev/) +* [http://mail-archives.apache.org/mod_mbox/mahout-user/](http://mail-archives.apache.org/mod_mbox/mahout-user/) + +<a name="MailingLists,IRCandArchives-ExternalArchives"></a> +## External Archives + +* [MarkMail](http://mahout.markmail.org/) +* [Gmane](http://dir.gmane.org/gmane.comp.apache.mahout.user) + +Please note the inclusion of a link to an archive does not imply an +endorsement of that company by any of the committers of Mahout the Lucene +PMC or the Apache Software Foundation. Each archive owner is solely +responsible for the contents and availability of their archive. http://git-wip-us.apache.org/repos/asf/mahout/blob/ec5eb314/website-old/oldsite/general/powered-by-mahout.md ---------------------------------------------------------------------- diff --git a/website-old/oldsite/general/powered-by-mahout.md b/website-old/oldsite/general/powered-by-mahout.md new file mode 100644 index 0000000..cb7c039 --- /dev/null +++ b/website-old/oldsite/general/powered-by-mahout.md @@ -0,0 +1,129 @@ +--- +layout: default +title: Powered By Mahout +theme: + name: retro-mahout +--- + +# Powered by Mahout + +Are you using Mahout to do Machine Learning? <a href="https://mahout.apache.org/general/mailing-lists,-irc-and-archives.html";>Care to share</a>? Developers of the project always are happy to learn about new happy users with interesting use cases. + +*Links here do NOT imply +endorsement by Mahout, its committers or the Apache Software Foundation and +are for informational purposes only.* + +<a name="PoweredByMahout-CommercialUse"></a> +## Commercial Use + +* <a href="http://nosql.mypopescu.com/post/2082712431/hbase-and-hadoop-at-adobe";>Adobe AMP</a> uses Mahout's clustering algorithms to increase video +consumption by better user targeting. +* Accenture uses Mahout as typical example for their [Hadoop Deployment Comparison Study](http://www.accenture.com/SiteCollectionDocuments/PDF/Accenture-Hadoop-Deployment-Comparison-Study.pdf) +* [AOL](http://www.aol.com) + use Mahout for shopping recommendations. See [slide deck](http://www.slideshare.net/kryton/the-data-layer) +* [Booz Allen Hamilton](http://www.boozallen.com/) + uses Mahout's clustering algorithms. See [slide deck](http://www.slideshare.net/ydn/3-biometric-hadoopsummit2010) +* [Buzzlogic](http://www.buzzlogic.com) + uses Mahout's clustering algorithms to improve ad targeting +* [Cull.tv](http://cull.tv/) + uses modified Mahout algorithms for content recommendations +*  [DataMine Lab](http://dataminelab.com) + uses Mahout's recommendation and clustering algorithms to improve our +clients' ad targeting. +* [Drupal](http://drupal.org/project/recommender) + uses Mahout to provide open source content recommendation solutions. +* [Evolv ](http://www.evolvondemand.com) + uses Mahout for its Workforce Predictive Analytics platform. +* [Foursquare](http://www.foursquare.com) + uses Mahout for its [recommendation engine](http://engineering.foursquare.com/2011/03/22/building-a-recommendation-engine-foursquare-style/). +* [Idealo](http://www.idealo.de) + uses Mahout's recommendation engine. +* [InfoGlutton](http://www.infoglutton.com) + uses Mahout's clustering and classification for various consulting +projects. +* [Intel](http://mark.chmarny.com/2013/07/thinking-big-about-data-at-intel.html) + ships Mahout as part of their Distribution for Apache Hadoop Software. +* [Intela](http://www.intela.com/) + has implementations of Mahout's recommendation algorithms to select new +offers to send tu customers, as well as to recommend potential customers to +current offers. We are also working on enhancing our offer categories by +using the clustering algorithms. +*  [iOffer](http://www.ioffer.com) + uses Mahout's Frequent Pattern Mining and Collaborative Filtering to +recommend items to users. +*  [Kauli](http://kau.li/en) +, one of Japanese Adnetwork, uses Mahout's clustering to handle clickstream +data for predicting audience's interests and intents. +* [Linked.In](http://linkedin.com) + Historically, we have used R for model training. We have recently started +experimenting with Mahout for model training and are excited about it - also see + <a href="https://www.quora.com/LinkedIn-Recommendations/How-does-LinkedIns-recommendation-system-work?srid=XoeG&share=1";>Hadoop World slides</a> +. +* [LucidWorks Big Data](http://www.lucidworks.com/products/lucidworks-big-data) + uses Mahout for clustering, duplicate document detection, phrase +extraction and classification. +*  [Mendeley](http://mendeley.com) + uses Mahout to power Mendeley Suggest, a research article recommendation +service. +*  [Mippin](http://mippin.com) + uses Mahout's collaborative filtering engine to recommend news feeds +* [Mobage](http://www.slideshare.net/hamadakoichi/mobage-prmu-2011-mahout-hadoop) + uses Mahout in their analysis pipeline +*  [Myrrix](http://myrrix.com) + is a recommender system product built on Mahout. +*  [NewsCred](http://platform.newscred.com) + uses Mahout to generate clusters of news articles and to surface the +important stories of the day +* [Next Glass](http://nextglass.co/) + uses Mahout +* [Predixion Software](http://predixionsoftware.com/) + uses Mahoutâs algorithms to build predictive models on big data +* <img src="http://www.radoop.eu/wp-content/uploads/favicon.png"; width=15> [Radoop](http://radoop.eu) + provides a drag-n-drop interface for big data analytics, including Mahout +clustering and classification algorithms +*  [ResearchGate](http://www.researchgate.net/), the professional network for scientists and researchers, uses Mahout's +recommendation algorithms. +* [Sematext](http://www.sematext.com/) + uses Mahout for its recommendation engine +* [SpeedDate.com](http://www.speeddate.com) + uses Mahout's collaborative filtering engine to recommend member profiles +* [Twitter](http://twitter.com) + uses Mahout's LDA implementation for user interest modeling +* [Yahoo\!](http://www.yahoo.com) + Mail uses Mahout's Frequent Pattern Set Mining. See [slides](http://www.slideshare.net/hadoopusergroup/mail-antispam) +* [365Media ](http://365media.com/) + uses *Mahout's* Classification and Collaborative Filtering algorithms in +its Real-time system named [UPTIME](http://uptime.365media.com/) + and 365Media/Social + +<a name="PoweredByMahout-AcademicUse"></a> +## Academic Use + +* [Dicode](https://www.dicode-project.eu/) + project uses Mahout's clustering and classification algorithms on top of +HBase. +* The course [Large Scale Data Analysis and Data Mining](http://www.dima.tu-berlin.de/menue/teaching/masterstudium/aim-3/) + at TU Berlin uses Mahout to teach students about the parallelization of data +mining problems with Hadoop and Map/Reduce +* Mahout is used at Carnegie Mellon University, as a comparable platform to [GraphLab](http://www.graphlab.ml.cmu.edu/) + +* The [ROBUST project](http://www.robust-project.eu/) +, co-funded by the European Commission, employs Mahout in the large scale +analysis of online community data. +* Mahout is used for research and data processing at [Nagoya Institute of Technology](http://www.nitech.ac.jp/eng/schools/grad/cse.html) +, in the context of a large-scale citizen participation platform project, +funded by the Ministry of Interior of Japan. +* Several researches within [Digital Enterprise Research Institute](http://www.deri.ie) + [NUI Galway](http://www.nuigalway.ie) + use Mahout for e.g. topic mining and modelling of large corpora. +* Mahout is used in the NoTube EU project. + +<a name="PoweredByMahout-PoweredByLogos"></a> +## Powered By Logos + +Feel free to use our **Powered By** logos on your site: + + + + + \ No newline at end of file http://git-wip-us.apache.org/repos/asf/mahout/blob/ec5eb314/website-old/oldsite/general/privacy-policy.md ---------------------------------------------------------------------- diff --git a/website-old/oldsite/general/privacy-policy.md b/website-old/oldsite/general/privacy-policy.md new file mode 100644 index 0000000..bc10929 --- /dev/null +++ b/website-old/oldsite/general/privacy-policy.md @@ -0,0 +1,28 @@ +--- +layout: default +title: Privacy Policy +theme: + name: retro-mahout +--- +Information about your use of this website is collected using server access +logs and a tracking cookie. The collected information consists of the +following: + +* The IP address from which you access the website; +* The type of browser and operating system you use to access our site; +* The date and time you access our site; +* The pages you visit; and +* The addresses of pages from where you followed a link to our site. + +Part of this information is gathered using a tracking cookie set by the +Google Analytics service and handled by Google as described in their +privacy policy. See your browser documentation for instructions on how to +disable the cookie if you prefer not to share this data with Google. + +We use the gathered information to help us make our site more useful to +visitors and to better understand how and when our site is used. We do not +track or collect personally identifiable information or associate gathered +data with any personally identifying information from other sources. + +By using this website, you consent to the collection of this data in the +manner and for the purpose described above. http://git-wip-us.apache.org/repos/asf/mahout/blob/ec5eb314/website-old/oldsite/general/professional-support.md ---------------------------------------------------------------------- diff --git a/website-old/oldsite/general/professional-support.md b/website-old/oldsite/general/professional-support.md new file mode 100644 index 0000000..ad8ef7c --- /dev/null +++ b/website-old/oldsite/general/professional-support.md @@ -0,0 +1,39 @@ +--- +layout: default +title: Professional Support +theme: + name: retro-mahout +--- + +<a name="ProfessionalSupport-ProfessionalsupportforMahout"></a> +# Professional support for Mahout + +Add yourself or your company if you are offering support for Mahout +users. Please keep lists in alphabetical order. An entry here +is not an endorsement by the Apache Software Foundation nor any of its +committers. + + +<a name="ProfessionalSupport-Peopleandcompaniesforhire"></a> +## People and companies for hire + +| Name | Contact details | Notes | +|------|-----------------|-------| +| Accenture | [email protected] | [Consulting services in big data analytics](http://accenture.com) | +| Boston Predictive Analytics | [email protected] | [http://tutorteddy.com/site/free_statistics_help.php](http://tutorteddy.com/site/free_statistics_help.php) | +| Frank Scholten | [email protected] | | +| GridLine | [http://www.gridline.nl/contact](http://www.gridline.nl/contact) | Specialised in search and thesauri | +| Jagdish Nomula | [email protected] | ML, Search, Algorithms, Java [http://www.kosmex.com](http://www.kosmex.com) | +| LucidWorks | [http://www.lucidworks.com](http://www.lucidworks.com) | Big data platform including Mahout as a service for clustering, classification and more | +| Sematext International | [http://sematext.com/](http://sematext.com/) | | +| Ted Dunning | [email protected] | Full commercial support | +| Winterwell | [email protected] | Business/maths concept development & algorithms [http://winterwell.com](http://winterwell.com) | + +<a name="ProfessionalSupport-Talksandpresentations"></a> +## Talks and presentations + +| Name | Contact details | Notes | +|------|-----------------|-------| +| Andrew Musselman | [email protected] | ["Building a Recommender with Apache Mahout on Amazon Elastic-MapReduce"](https://blogs.aws.amazon.com/bigdata/post/Tx1TDK3HHBD4EZL/Building-a-Recommender-with-Apache-Mahout-on-Amazon-Elastic-MapReduce-EMR) | +| Frank Scholten | [email protected] | Mahout/Taste [http://blog.jteam.nl/author/frank/](http://blog.jteam.nl/author/frank/) | +| Isabel Drost-Fromm | [email protected] | If travel and accommodation costs are covered scheduling a talk is a lot easier. | http://git-wip-us.apache.org/repos/asf/mahout/blob/ec5eb314/website-old/oldsite/general/reference-reading.md ---------------------------------------------------------------------- diff --git a/website-old/oldsite/general/reference-reading.md b/website-old/oldsite/general/reference-reading.md new file mode 100644 index 0000000..ba969ac --- /dev/null +++ b/website-old/oldsite/general/reference-reading.md @@ -0,0 +1,71 @@ +--- +layout: default +title: Reference Reading +theme: + name: retro-mahout +--- + +# Reference Reading + +Here we provide references to books and courses about data analysis in general, which might also be helpful in the context of Mahout. + +<a name="ReferenceReading-GeneralBackgroundMaterials"></a> +## General Background Materials + +Don't be overwhelmed by all the maths, you can do a lot in Mahout with some +basic knowledge. The books will help you understand your +data better, and ask better questions both of Mahout's APIs, and also of +the Mahout community. And unlike learning some particular software tool, +these are skills that will remain useful decades later. + + * [Gilbert Strang](http://www-math.mit.edu/~gs) +'s [Introduction to Linear Algebra](http://math.mit.edu/linearalgebra/). His [lectures](http://ocw.mit.edu/courses/mathematics/18-06-linear-algebra-spring-2010/) are also [available online](http://web.mit.edu/18.06/www/) + and are strongly recommended. + * [Mathematical Tools for Applied Mulitvariate Analysis](http://www.amazon.com/Mathematical-Tools-Applied-Multivariate-Analysis/dp/0121609553/ref=sr_1_1?ie=UTF8&qid=1299602805&sr=8-1) by J.Douglass +Carroll. + * [Stanford Machine Learning online courseware](http://www.stanford.edu/class/cs229/) + * [MIT Machine Learning online courseware](http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-867-machine-learning-fall-2006/) has [lecture notes](http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-867-machine-learning-fall-2006/lecture-notes/) online. + * As a pre-requisite to probability and statistics, you'll need [basic calculus](http://en.wikipedia.org/wiki/Calculus). A maths for scientists text might be useful here such as 'Mathematics for Engineers and Scientists', Alan Jeffrey, Chapman & Hall/CRC. ([openlibrary](http://openlibrary.org/books/OL3305993M/Mathematics_for_engineers_and_scientists)) + * One of the best writers in the probability/statistics world is Sheldon Ross. Try [A First Course in Probability (8th Edition)](http://www.pearsonhighered.com/educator/product/First-Course-in-Probability-A/9780136033134.page) and then move on to his [Introduction to Probability Models](http://www.amazon.com/Introduction-Probability-Models-Sixth-Sheldon/dp/0125984707) + +Some good introductory alternatives here are: + + * [Kahn Academy](http://www.khanacademy.org/) -- videos on stats, probability, linear algebra + * [Probability and Statistics (7th Edition)](http://www.amazon.com/Probability-Statistics-Engineering-Sciences-InfoTrac/dp/0534399339), Jay L. Devore, Chapman. + * [Probability and Statistical Inference (7th Edition)](http://www.amazon.com/Probability-Statistical-Inference-Robert-Hogg/dp/0132546086), Hogg and Tanis, Pearson. + +Once you have a grasp of the basics then there are a slew of great texts that you might consult: + + * [Statistical Inference](http://www.amazon.com/Statistical-Inference-George-Casella/dp/0534243126), Casell and Berger, Duxbury/Thomson Learning. + * [Introduction to Bayesian Statistics](http://www.amazon.com/Introduction-Bayesian-Statistics-William-Bolstad/dp/0471270202), William H. Bolstad, Wiley. + * [Understanding Computational Bayesian Statistics](http://www.amazon.com/Understanding-Computational-Bayesian-Statistics-Wiley/dp/0470046090), Bolstadt + * [Bayesian Data Analysis, Gelman et al.](http://www.stat.columbia.edu/~gelman/book/) + + +## For statistics related to machine learning, these are particularly helpful: + + * [Pattern Recognition and Machine Learning by Chris Bishop](http://research.microsoft.com/en-us/um/people/cmbishop/PRML/index.htm) + * [Elements of Statistical Learning](http://www-stat.stanford.edu/~tibs/ElemStatLearn/) by Trevor Hastie, Robert Tibshirani, Jerome Friedman + * [http://research.microsoft.com/en-us/um/people/cmbishop/PRML/index.htm](http://research.microsoft.com/en-us/um/people/cmbishop/PRML/index.htm) + + +## For matrix computations/decomposition/factorization etc.: + + * Peter V. O'Neil [Introduction to Linear Algebra](http://www.amazon.com/Introduction-Linear-Algebra-Theory-Applications/dp/053400606X), great book for beginners (with some knowledge in calculus). It is not comprehensive, but, it will be a good place to start and the author starts by explaining the concepts with regards to vector spaces which I found to be a more natural way of explaining. + * David S. Watkins [Fundamentals of Matrix Computations](http://www.amazon.com/Fundamentals-Matrix-Computations-Applied-Mathematics/dp/0470528338/) + * [Matrix Computations](http://www.amazon.com/Computations-Hopkins-Studies-Mathematical-Sciences/dp/0801854148/ref=sr_1_2?s=books&ie=UTF8&qid=1394307676&sr=1-2&keywords=golub+van+loan) is the classic text for numerical linear algebra. Can't go wrong with it - great for researchers. + * Nick Trefethen's [Numerical Linear Algebra](http://people.maths.ox.ac.uk/trefethen/books.html). It's a bit more approachable for practitioners. Many chapters on SVD, there are even chapters on Lanczos. + + +## Books specifically on R: + +* Learning about R is a difficult thing. The best introduction is in MASS [http://www.stats.ox.ac.uk/pub/MASS4/](http://www.stats.ox.ac.uk/pub/MASS4/) +* [R Tutor](http://www.r-tutor.com/r-introduction) +* [Manual](http://cran.r-project.org/doc/manuals/R-intro.pdf) +* [R Course](http://faculty.washington.edu/tlumley/Rcourse/) + +In addition, you should see how to plot data well: + +* [Trellis plotting](http://www.statmethods.net/advgraphs/trellis.html) +* [ggplot2](http://had.co.nz/ggplot2/) + http://git-wip-us.apache.org/repos/asf/mahout/blob/ec5eb314/website-old/oldsite/general/release-notes.md ---------------------------------------------------------------------- diff --git a/website-old/oldsite/general/release-notes.md b/website-old/oldsite/general/release-notes.md new file mode 100644 index 0000000..bd41ebb --- /dev/null +++ b/website-old/oldsite/general/release-notes.md @@ -0,0 +1,242 @@ +--- +layout: default +title: Release Notes +theme: + name: retro-mahout +--- + +# Release Notes + +#### 11 April 2016 - Apache Mahout 0.12.0 released + +This release marks a major milestone for the âSamsaraâ environmentâs goal +of providing an engine neutral math platform by now supporting Apache Flink. +While still experimental, the mahout Flink bindings now offer all of the R-Like +semantics for linear algebra operations, matrix decompositions, +and algorithms of the âSamsaraâ platform for execution on a Flink back-end. + +This release gives users of Apache Flink out of the box access to the following features (and more): + +<ol> +<li>The Mahout Distributed Row Matrix (DRM) API.</li> +<li>Distributed and local Vector and Matrix algebra routines.</li> +<li>Distributed and local Stochastic Principal Component Analysis.</li> +<li>Distributed and local Stochastic Singular Value Decomposition.</li> +<li>Distributed and local Thin QR Decomposition.</li> +<li>Collaborative Filtering.</li> +<li>Naive Bayes Classification.</li> +<li>Matrix operations (only listing a few here): +<ol> +<li>Mahout-native blockified distributed Matrix map and allreduce routines.</li> +<li>Distributed data point (row) sampling.</li> +<li>Matrix/Matrix Squared Distance.</li> +<li>Element-wise log.</li> +<li>Element-wise roots.</li> +<li>Element-wise Matrix/Matrix addition, subtraction, division and multiplication.</li> +<li>Functional Matrix value assignment.</li> +<li>A familiar Scala-based R-like DSL.</li> +</ol> +</ol> + +#### 11 March 2016 - Apache Mahout 0.11.2 released + +This is a minor release over Mahout 0.11.1 meant to introduce major +performance enhancements with sparse matrix and vector computations, and +major performance optimizations to the Samsara DSL. Mahout 0.11.2 includes +all new features and bug fixes released in Mahout versions 0.11.0 and +0.11.1. + +Highlights include: + +* Spark 1.5.2 support +* Performance improvements of over 30% on Sparse Vector and Matrix + computations leveraging the âfastutilâ library - contribution from + Sebastiano Vigna. This speeds up all in-core sparse vector and matrix + computations. + + +#### 06 November 2015 - Apache Mahout 0.11.1 released + +This is a minor release over Mahout 0.11.0 meant to expand Mahoutâs +compatibility with Spark versions, to introduce some new features and to +fix some bugs. Mahout 0.11.1 includes all new features and bug fixes +released in Mahout versions 0.11.0 and earlier. + +Highlights include: + +* Spark 1.4+ support +* 4x Performance improvement in Dot Product over Dense Vectors (https://issues.apache.org/jira/browse/MAHOUT-1781) + + +#### 07 August 2015 - Apache Mahout 0.11.0 released + +Mahout 0.11.0 includes all new features and bugfixes released in Mahout versions 0.10.1 +and 0.10.2 along with support for Spark 1.3+. + +Highlights include: + +* Spark 1.3 support +* Fixes for a major memory usage bug in co-occurrence analysis used by the driver spark-itemsimilarity. This will now require far less memory in the executor. +* Some minor fixes to Mahout-Samsara QR Decomposition and matrix ops. +* All of the Mahout Samsara fixes from 0.10.2 Release + + +#### 06 August 2015 - Apache Mahout 0.10.2 released + +Highlights include: + +* In-core transpose view rewrites. Modifiable transpose views eg. (for (col <- a.t) col := 5). +* Performance and parallelization improvements for AB', A'B, A'A spark physical operators. +* Optional structural "flavor" abstraction for in-core matrices. In-core matrices can now be tagged as e.g. sparse or dense. +* %*% optimization based on matrix flavors. +* In-core ::= sparse assignment functions. +* Assign := optimization (do proper traversal based on matrix flavors, similarly to %*%). +* Adding in-place elementwise functional assignment (e.g. mxA := exp _, mxA ::= exp _). +* Distributed and in-core version of simple elementwise analogues of scala.math._. for example, for log(x) the convention is dlog(drm), mlog(mx), vlog(vec). Unfortunately we cannot overload these functions over what is done in scala.math, i.e. scala would not allow log(mx) or log(drm) and log(Double) at the same time, mainly because they are being defined in different packages. +* Distributed and in-core first and second moment routines. R analogs: mean(), colMeans(), rowMeans(), variance(), sd(). By convention, distributed versions are prepended by (d) letter: colMeanVars() colMeanStdevs() dcolMeanVars() dcolMeanStdevs(). +* Distance and squared distance matrix routines. R analog: dist(). Provide both squared and non-squared Euclidean distance matrices. By convention, distributed versions are prepended by (d) letter: dist(x), sqDist(x), dsqDist(x). Also a variation for pair-wise distance matrix of two different inputs x and y: sqDist(x,y), dsqDist(x,y). +* DRM row sampling api. +* Distributed performance bug fixes. This relates mostly to (a) matrix multiplication deficiencies, and (b) handling parallelism. +* Distributed engine neutral allreduceBlock() operator api for Spark and H2O. +* Distributed optimizer operators for elementwise functions. Rewrites recognizing e.g. 1+ drmX * dexp(drmX) as a single fused elementwise physical operator: elementwiseFunc(f1(f2(drmX)) where f1 = 1 + x and f2 = exp(x). +* More cbind, rbind flavors (e.g. 1 cbind mxX, 1 cbind drmX or the other way around) for Spark and H2O. +* Added +=: and *=: operators on vectors. +* Closeable API for broadcast tensors. +* Support for conversion of any type-keyed DRM into ordinally-keyed DRM. +* Scala logging style. +* rowSumsMap() summary for non-int-keyed DRMs. +* elementwise power operator ^ . +* R-like vector concatenation operator. +* In-core functional assignments e.g.: mxA := { (x) => x * x}. +* Straighten out behavior of Matrix.iterator() and iterateNonEmpty(). +* New mutable transposition view for in-core matrices. In-core matrix transpose view. rewrite with mostly two goals in mind: (1) enable mutability, e.g. for (col <- mxA.t) col := k (2) translate matrix structural flavor for optimizers correctly. i.e. new SparseRowMatrix.t carries on as column-major structure. +* Native support for kryo serialization of tensor types. +* Deprecation of the MultiLayerPerceptron, ConcatenateVectorsJob and all related classes. +* Deprecation of SparseColumnMatrix. + +#### 31 May 2015 - Apache Mahout 0.10.1 released + +Highlights include: + +* Major memory use improvements in cooccurrence analysis including the spark-itemsimilarity driver [MAHOUT-1707](https://issues.apache.org/jira/browse/MAHOUT-1707) +* Support for Spark version 1.2.2 or less. +* Some minor fixes to Mahout-Samsara QR Decomposition and matrix ops. +* Trim down packages size to < 200MB MAHOUT-1704 and MAHOUT-1706 +* Minor testing indicates binary compatibility with Spark 1.3 with the exception of the Mahout Shell. + +#### 11 April 2015 - Apache Mahout 0.10.0 released + +Mahout 0.10.0 was a major release, which separates out a ML environment (we call Mahout-Samsara) including an +extended version of Scala that is largely backend independent but runs fully on Spark. The Hadoop MapReduce versions of +Mahout algorithms are still maintained but no new MapReduce contributions are accepted. From this release onwards +contributions must be Mahout Samsara based or at least run on Spark. + +Highlights include: + +New Mahout Samsara Environment + +* Distributed Algebraic optimizer +* R-Like DSL Scala API +* Linear algebra operations +* Ops are extensions to Scala +* Scala REPL based interactive shell running on Spark +* Integrates with compatible libraries like MLlib +* Run on distributed Spark +* H2O in progress + +New Mahout Samsara based Algorithms + +* Stochastic Singular Value Decomposition (ssvd, dssvd) +* Stochastic Principal Component Analysis (spca, dspca) +* Distributed Cholesky QR (thinQR) +* Distributed regularized Alternating Least Squares (dals) +* Collaborative Filtering: Item and Row Similarity +* Naive Bayes Classification +* Distributed and in-core + +Changes in 0.10.0 are detailed <a href="https://github.com/apache/mahout/blob/mahout-0.10.0/CHANGELOG";>here</a> + +#### 1 February 2014 - Apache Mahout 0.9 released + + <p>Highlights include:</p> + + <ul> + <li>New and improved Mahout website based on Apache CMS - <a href="https://issues.apache.org/jira/browse/MAHOUT-1245";>MAHOUT-1245</a></li> + <li>Early implementation of a Multi Layer Perceptron (MLP) classifier - <a href="https://issues.apache.org/jira/browse/MAHOUT-1265";>MAHOUT-1265</a>.</li> + <li>Scala DSL Bindings for Mahout Math Linear Algebra. See <a href="http://weatheringthrutechdays.blogspot.com/2013/07/scala-dsl-for-mahout-in-core-linear.html";>this blogpost</a> - <a href="https://issues.apache.org/jira/browse/MAHOUT-1297";>MAHOUT-1297</a></li> + <li>Recommenders as a Search. See <a href="https://github.com/pferrel/solr-recommender";>https://github.com/pferrel/solr-recommender</a> - <a href="https://issues.apache.org/jira/browse/MAHOUT-1288";>MAHOUT-1288</a></li> + <li>Support for easy functional Matrix views and derivatives - <a href="https://issues.apache.org/jira/browse/MAHOUT-1300";>MAHOUT-1300</a></li> + <li>JSON output format for ClusterDumper - <a href="https://issues.apache.org/jira/browse/MAHOUT-1343";>MAHOUT-1343</a></li> + <li>Enable randomised testing for all Mahout modules using Carrot RandomizedRunner - <a href="https://issues.apache.org/jira/browse/MAHOUT-1345";>MAHOUT-1345</a></li> + <li>Online Algorithm for computing accurate Quantiles using 1-dimensional Clustering - <a href="https://issues.apache.org/jira/browse/MAHOUT-1361";>MAHOUT-1361</a>. See this <a href="https://github.com/tdunning/t-digest/blob/master/docs/theory/t-digest-paper/histo.pdf";>pdf</a> for the details. + <li>Upgrade to Lucene 4.6.1 - <a href="https://issues.apache.org/jira/browse/MAHOUT-1364";>MAHOUT-1364</a></li> + </ul> + + <p>Changes in 0.9 are detailed <a href="http://svn.apache.org/viewvc/mahout/trunk/CHANGELOG?view=markup&pathrev=1563661";>here</a>.</p> + +#### 25 July 2013 - Apache Mahout 0.8 released + + <p>Highlights include:</p> + + <ul> + <li>Numerous performance improvements to Vector and Matrix implementations, API's and their iterators</li> + <li>Numerous performance improvements to the recommender implementations</li> + <li><a href="https://issues.apache.org/jira/browse/MAHOUT-1088"; class="external-link" rel="nofollow">MAHOUT-1088</a>: Support for biased item-based recommender</li> + <li><a href="https://issues.apache.org/jira/browse/MAHOUT-1089"; class="external-link" rel="nofollow">MAHOUT-1089</a>: SGD matrix factorization for rating prediction with user and item biases</li> + <li><a href="https://issues.apache.org/jira/browse/MAHOUT-1106"; class="external-link" rel="nofollow">MAHOUT-1106</a>: Support for SVD++</li> + <li><a href="https://issues.apache.org/jira/browse/MAHOUT-944"; class="external-link" rel="nofollow">MAHOUT-944</a>: Support for converting one or more Lucene storage indexes to SequenceFiles as well as an upgrade of the supported Lucene version to Lucene 4.3.1.</li> + <li><a href="https://issues.apache.org/jira/browse/MAHOUT-1154"; class="external-link" rel="nofollow">MAHOUT-1154</a> and friends: New streaming k-means implementation that offers on-line (and fast) clustering</li> + <li><a href="https://issues.apache.org/jira/browse/MAHOUT-833"; class="external-link" rel="nofollow">MAHOUT-833</a>: Make conversion to SequenceFiles Map-Reduce, 'seqdirectory' can now be run as a MapReduce job.</li> + <li><a href="https://issues.apache.org/jira/browse/MAHOUT-1052"; class="external-link" rel="nofollow">MAHOUT-1052</a>: Add an option to MinHashDriver that specifies the dimension of vector to hash (indexes or values).</li> + <li><a href="https://issues.apache.org/jira/browse/MAHOUT-884"; class="external-link" rel="nofollow">MAHOUT-884</a>: Matrix Concat utility, presently only concatenates two matrices.</li> + <li><a href="https://issues.apache.org/jira/browse/MAHOUT-1187"; class="external-link" rel="nofollow">MAHOUT-1187</a>: Upgraded to CommonsLang3</li> + <li><a href="https://issues.apache.org/jira/browse/MAHOUT-916"; class="external-link" rel="nofollow">MAHOUT-916</a>: Speedup the Mahout build by making tests run in parallel.</li> + + </ul> + + <p>Changes in 0.8 are detailed <a href="http://svn.apache.org/viewvc/mahout/trunk/CHANGELOG?revision=1501110&view=markup";>here</a>.</p> + +#### 16 June 2012 - Apache Mahout 0.7 released + + <p>Highlights include:</p> + + <ul> + <li>Outlier removal capability in K-Means, Fuzzy K, Canopy and Dirichlet Clustering</li> + <li>New Clustering implementation for K-Means, Fuzzy K, Canopy and Dirichlet using Cluster Classifiers</li> + <li>Collections and Math API consolidated</li> + <li>(Complementary) Naive Bayes refactored and cleaned</li> + <li>Watchmaker and Old Naive Bayes dropped.</li> + <li>Many bug fixes, refactorings, and other small improvements</li> + </ul> + + <p>Changes in 0.7 are detailed <a href="https://issues.apache.org/jira/secure/ReleaseNote.jspa?projectId=12310751&version=12319261";>here</a>.</p> + + + +#### 6 Feb 2012 - Apache Mahout 0.6 released + + <p>Highlights include:</p> + + <ul> + <li>Improved Decision Tree performance and added support for regression problems</li> + <li>New LDA implementation using Collapsed Variational Bayes 0th Derivative Approximation</li> + <li>Reduced runtime of LanczosSolver tests</li> + <li>K-Trusses, Top-Down and Bottom-Up clustering, Random Walk with Restarts implementation</li> + <li>Reduced runtime of dot product between vectors</li> + <li>Added MongoDB and Cassandra DataModel support</li> + <li>Increased efficiency of parallel ALS matrix factorization</li> + <li>SSVD enhancements</li> + <li>Performance improvements in RowSimilarityJob, TransposeJob</li> + <li>Added numerous clustering display examples</li> + <li>Many bug fixes, refactorings, and other small improvements</li> + </ul> + + <p>Changes in 0.6 are detailed <a href="https://issues.apache.org/jira/secure/ReleaseNote.jspa?projectId=12310751&version=12316364";>here</a>.</p> + +#### Past Releases + + * [Mahout 0.5](https://issues.apache.org/jira/secure/ReleaseNote.jspa?version=12315255&styleName=Text&projectId=12310751&Create=Create&atl_token=A5KQ-2QAV-T4JA-FDED|20f0d06214912accbd47acf2f0a89231ed00a767|lin) + * [Mahout 0.4](https://issues.apache.org/jira/secure/ReleaseNote.jspa?version=12314281&styleName=Text&projectId=12310751&Create=Create&atl_token=A5KQ-2QAV-T4JA-FDED|20f0d06214912accbd47acf2f0a89231ed00a767|lin) + * [Mahout 0.3](https://issues.apache.org/jira/secure/ReleaseNote.jspa?version=12314281&styleName=Text&projectId=12310751&Create=Create&atl_token=A5KQ-2QAV-T4JA-FDED|20f0d06214912accbd47acf2f0a89231ed00a767|lin) + * [Mahout 0.2](https://issues.apache.org/jira/secure/ReleaseNote.jspa?version=12313278&styleName=Text&projectId=12310751&Create=Create&atl_token=A5KQ-2QAV-T4JA-FDED|20f0d06214912accbd47acf2f0a89231ed00a767|lin) + * [Mahout 0.1](https://issues.apache.org/jira/secure/ReleaseNote.jspa?version=12312976&styleName=Html&projectId=12310751&Create=Create&atl_token=A5KQ-2QAV-T4JA-FDED%7C48e83cdefb8bca42acf8f129692f8c3a05b360cf%7Clout) \ No newline at end of file http://git-wip-us.apache.org/repos/asf/mahout/blob/ec5eb314/website-old/oldsite/general/who-we-are.md ---------------------------------------------------------------------- diff --git a/website-old/oldsite/general/who-we-are.md b/website-old/oldsite/general/who-we-are.md new file mode 100644 index 0000000..24f493b --- /dev/null +++ b/website-old/oldsite/general/who-we-are.md @@ -0,0 +1,62 @@ +--- +layout: default +title: Who We Are +theme: + name: retro-mahout +--- + +<a name="WhoWeAre-Whoweare"></a> +# Who we are + +Apache Mahout is maintained by a team of volunteer developers. + +<a name="WhoWeAre-CoreCommitters"></a> +## Core Committers + +(Please keep the list below in alphabetical order by first name.) + +Name | Mail | PMC | Comment +----|---------|------|------|---------- +Anand Avati | avati@... | No | Twitter: @anandavati +Andrew Musselman | akm@... | Yes | Twitter: @akm +Andrew Palumbo | apalumbo@... | Yes (Chair) | | +Benson Margulies | bimargulies@... | Yes | | +Dan Filimon | dfilimon@... | No | | +Dmitriy Lyubimov | dlyubimov@... | No (Emeritus) | +Drew Farris | drew@... | Yes | | +Ellen Friedman | ellenf@... | No | Twitter: @Ellen_Friedman +Frank Scholten | frankscholten@... | No | | +Gokhan Capan | gcapan@... | No | <a href="http://www.linkedin.com/in/gokhancapan";>LinkedIn Profile</a> +Grant Ingersoll | gsingers@... | Yes | Twitter: @gsingers +Isabel Drost-Fromm | isabel@... | Yes | Passion for free software (development, but to some extend also the political and economic implications), interested in agile development and project management, lives in Germany. Follow me on Twitter @MaineC +Jacob Alexander Mannix | jmannix@... | Yes | | +Jeff Eastman | jeastman@... | No (Emeritus) | +Paritosh Ranjan | pranjan@... | Yes | Twitter: @paritoshranjan +Pat Ferrel | pat@... | Yes | Twitter: @occam +Robin Anil | robinanil@... | Yes | | +Sean Owen | srowen@... | No (Emeritus) | +Sebastian Schelter | ssc@... | Yes | | +Shannon Quinn | squinn@... | No | | +Stevo SlaviÄ| sslavic@... | No | Twitter: @sslavic +Suneel Marthi | smarthi@... | Yes | Twitter: @suneelmarthi +Ted Dunning | tdunning@... | Yes | +Tom Pierce | tcp@... | No | | + +<a name="WhoWeAre-EmeritusCommitters"></a> +## Emeritus Committers + +* Niranjan Balasubramanian (nbalasub@...) +* Otis Gospodnetic (otis@...) +* David Hall (dlwh@...) +* Erik Hatcher (ehatcher@...) +* Ozgur Yilmazel (oyilmazel@...) +* Dawid Weiss (dweiss@...) +* Karl Wettin (kalle@...) +* AbdelHakim Deneche (adeneche@...) + +Note that the email addresses above end with @apache.org. + +<a name="WhoWeAre-Contributors"></a> 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