Repository: mahout Updated Branches: refs/heads/website 0e718ec99 -> 3a724debc
http://git-wip-us.apache.org/repos/asf/mahout/blob/3a724deb/website/front/community/blogs.md ---------------------------------------------------------------------- diff --git a/website/front/community/blogs.md b/website/front/community/blogs.md new file mode 100644 index 0000000..7ddd0ac --- /dev/null +++ b/website/front/community/blogs.md @@ -0,0 +1,18 @@ +--- +layout: default +title: History of Apache Mahout +theme: + name: mahout2 +--- + +<!-- Add to this collection, newest date on top in following format: +### [Title](Link to Post) +**Author**, _MM/DD/YYYY_, Name of Host +Description +--> + +### [Getting Started With Apache Mahout](https://datascience.ibm.com/blog/getting-started-with-apache-mahout-2/) +**Trevor Grant** | _04/25/2017_ | datascience.ibm.com/blog + +How to setup Apache Mahout in IBM's Datascience Experience Notebooking Environment, and run a few trivial programs. + http://git-wip-us.apache.org/repos/asf/mahout/blob/3a724deb/website/front/community/books-tutorials-and-talks.md ---------------------------------------------------------------------- diff --git a/website/front/community/books-tutorials-and-talks.md b/website/front/community/books-tutorials-and-talks.md deleted file mode 100644 index 67f5bef..0000000 --- a/website/front/community/books-tutorials-and-talks.md +++ /dev/null @@ -1,122 +0,0 @@ ---- -layout: default -title: Books, Tutorials, and Talks -theme: - name: mahout2 ---- - -# 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/3a724deb/website/front/community/buildingmahout.md ---------------------------------------------------------------------- diff --git a/website/front/community/buildingmahout.md b/website/front/community/buildingmahout.md index 0363954..f6e33d2 100644 --- a/website/front/community/buildingmahout.md +++ b/website/front/community/buildingmahout.md @@ -6,12 +6,12 @@ theme: --- -# Building Mahout from source +# Building Mahout from Source ## Prerequisites * Java JDK 1.7 -* Apache Maven 3.3.3 +* Apache Maven 3.3.9 ## Getting the source code @@ -24,40 +24,105 @@ or git clone https://github.com/apache/mahout.git -##Hadoop version -Mahout code depends on hadoop-client artifact, with the default version 2.4.1. To build Mahout against to a -different hadoop version, hadoop.version property should be set accordingly and passed to the build command. -Hadoop1 clients would additionally require hadoop1 profile to be activated. +## Building From Source -The build lifecycle is illustrated below. +###### Prerequisites: -## Compiling +Linux Environment (preferably Ubuntu 16.04.x) Note: Currently only the JVM-only build will work on a Mac. +gcc > 4.x +NVIDIA Card (installed with OpenCL drivers alongside usual GPU drivers) -Compile Mahout using standard maven commands +###### Downloads - # With hadoop-2.4.1 dependency - mvn clean compile +Install java 1.7+ in an easily accessible directory (for this example, ~/java/) +http://www.oracle.com/technetwork/java/javase/downloads/jdk8-downloads-2133151.html + +Create a directory ~/apache/ . + +Download apache Maven 3.3.9 and un-tar/gunzip to ~/apache/apache-maven-3.3.9/ . +https://maven.apache.org/download.cgi + +Download and un-tar/gunzip Hadoop 2.4.1 to ~/apache/hadoop-2.4.1/ . +https://archive.apache.org/dist/hadoop/common/hadoop-2.4.1/ - # With hadoop-1.2.1 dependency - mvn -Phadoop1 -Dhadoop.version=1.2.1 clean compile +Download and un-tar/gunzip spark-1.6.3-bin-hadoop2.4 to ~/apache/ . +http://spark.apache.org/downloads.html +Choose release: Spark-1.6.3 (Nov 07 2016) +Choose package type: Pre-Built for Hadoop 2.4 -##Packaging +Install ViennaCL 1.7.0+ +If running Ubuntu 16.04+ -Mahout has an extensive test suite which takes some time to run. If you just want to build Mahout, skip the tests like this +``` +sudo apt-get install libviennacl-dev +``` - # With hadoop-2.4.1 dependency - mvn -DskipTests=true clean package +Otherwise if your distributionâs package manager does not have a viennniacl-dev package >1.7.0, clone it directly into the directory which will be included in when being compiled by Mahout: - # With hadoop-1.2.1 dependency - mvn -Phadoop1 -Dhadoop.version=1.2.1 -DskipTests=true clean package +``` +mkdir ~/tmp +cd ~/tmp && git clone https://github.com/viennacl/viennacl-dev.git +cp -r viennacl/ /usr/local/ +cp -r CL/ /usr/local/ +``` +Ensure that the OpenCL 1.2+ drivers are installed (packed with most consumer grade NVIDIA drivers). Not sure about higher end cards. -In order to add mahout artifact to your local repository, run +Clone mahout repository into `~/apache`. - # With hadoop-2.4.1 dependency - mvn clean install +``` +git clone https://github.com/apache/mahout.git +``` - # With hadoop-1.2.1 dependency - mvn -Phadoop1 -Dhadoop.version=1.2.1 clean install +###### Configuration +When building mahout for a spark backend, we need four System Environment variables set: +``` + export MAHOUT_HOME=/home/<user>/apache/mahout + export HADOOP_HOME=/home/<user>/apache/hadoop-2.4.1 + export SPARK_HOME=/home/<user>/apache/spark-1.6.3-bin-hadoop2.4 + export JAVA_HOME=/home/<user>/java/jdk-1.8.121 +``` + +Mahout on Spark regularly uses one more env variable, the IP of the Spark clusterâs master node (usually the node which one would be logged into). + +To use 4 local cores (Spark master need not be running) +``` +export MASTER=local[4] +``` +To use all available local cores (again, Spark master need not be running) +``` +export MASTER=local[*] +``` +To point to a cluster with spark running: +``` +export MASTER=spark://master.ip.address:7077 +``` + +We then add these to the path: + +``` + PATH=$PATH$:MAHOUT_HOME/bin:$HADOOP_HOME/bin:$SPARK_HOME/bin:$JAVA_HOME/bin +``` + +These should be added to the your ~/.bashrc file. + + +###### Building Mahout with Apache Maven + +Currently Mahout has 3 builds. From the $MAHOUT_HOME directory we may issue the commands to build each using mvn profiles. + +JVM only: +``` +mvn clean install -DskipTests +``` + +JVM with native OpenMP level 2 and level 3 matrix/vector Multiplication +``` +mvn clean install -Pviennacl-omp -Phadoop2 -DskipTests +``` +JVM with native OpenMP and OpenCL for Level 2 and level 3 matrix/vector Multiplication. (GPU errors fall back to OpenMP, currently only a single GPU/node is supported). +``` +mvn clean install -Pviennacl -Phadoop2 -DskipTests +``` \ No newline at end of file http://git-wip-us.apache.org/repos/asf/mahout/blob/3a724deb/website/front/community/faq.md ---------------------------------------------------------------------- diff --git a/website/front/community/faq.md b/website/front/community/faq.md deleted file mode 100644 index 2a17796..0000000 --- a/website/front/community/faq.md +++ /dev/null @@ -1,105 +0,0 @@ ---- -layout: default -title: Frequently Asked Questions -theme: - name: mahout2 ---- - -# 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/3a724deb/website/front/community/glossary.mdtext ---------------------------------------------------------------------- diff --git a/website/front/community/glossary.mdtext b/website/front/community/glossary.mdtext deleted file mode 100644 index 95757fb..0000000 --- a/website/front/community/glossary.mdtext +++ /dev/null @@ -1,6 +0,0 @@ -Title: Glossary -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/3a724deb/website/front/community/gsoc.md ---------------------------------------------------------------------- diff --git a/website/front/community/gsoc.md b/website/front/community/gsoc.md index 0b143f7..125a567 100644 --- a/website/front/community/gsoc.md +++ b/website/front/community/gsoc.md @@ -38,11 +38,10 @@ paid. personal (most things are not). This will likely decrease your chances of being selected, not increase them. * DO NOT BITE OFF MORE THAN YOU CAN CHEW. Every year, there are a few -students who propose to implement 3-5 machine learning algorithms on -Map/Reduce, all in a two month period. They NEVER get selected. Be +students who propose to implement 3-5 machine learning algorithms, all in a two month period. They NEVER get selected. Be realistic. All successful projects to date follow, more or less, the -following formula: Implement algorithm on Map/Reduce. Write Unit Tests. -Do some bigger scale tests. Write 1 or 2 examples. Write Wiki +following formula: Implement algorithm in Samsara (Mahout's R-Like Scala DSL). Write Unit Tests. +Do some bigger scale tests. Write 1 or 2 examples. Write Website documentation. That's it. Trust us, it takes a summer to do these things. http://git-wip-us.apache.org/repos/asf/mahout/blob/3a724deb/website/front/community/history.md ---------------------------------------------------------------------- diff --git a/website/front/community/history.md b/website/front/community/history.md new file mode 100644 index 0000000..bebc2f9 --- /dev/null +++ b/website/front/community/history.md @@ -0,0 +1,20 @@ +--- +layout: default +title: History of Apache Mahout +theme: + name: mahout2 +--- + + +TODO: Would really like to get perspective of multiple people here + +## Pre-Apache + +## Decision to Move to ASF + +## Early Releases + +## The 0.9.x Major Vendor Freeze + +## Mahout Samsara 0.10.0+ + http://git-wip-us.apache.org/repos/asf/mahout/blob/3a724deb/website/front/community/mahout-benchmarks.md ---------------------------------------------------------------------- diff --git a/website/front/community/mahout-benchmarks.md b/website/front/community/mahout-benchmarks.md deleted file mode 100644 index 1383e0a..0000000 --- a/website/front/community/mahout-benchmarks.md +++ /dev/null @@ -1,153 +0,0 @@ ---- -layout: default -title: Mahout Benchmarks -theme: - name: mahout2 ---- - -<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/3a724deb/website/front/community/mahout-wiki.md ---------------------------------------------------------------------- diff --git a/website/front/community/mahout-wiki.md b/website/front/community/mahout-wiki.md deleted file mode 100644 index e11dd0c..0000000 --- a/website/front/community/mahout-wiki.md +++ /dev/null @@ -1,200 +0,0 @@ ---- -layout: default -title: Mahout Wiki -theme: - name: mahout2 ---- - -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](/community/overview.html) - -- Mahout? What's that supposed to be? - -[Quickstart](/community/quickstart.html) - -- learn how to quickly setup Apache Mahout for your project. - -[FAQ](/community/faq.html) - -- Frequent questions encountered on the mailing lists. - -[Developer Resources](/developers/developer-resources.html) - -- overview of the Mahout development infrastructure. - -[How To Contribute](/developers/how-to-contribute.html) - -- get involved with the Mahout community. - -[How To Become A Committer](/developers/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](/community/who-we-are.html) - -- who are the developers behind Apache Mahout? - -[Books, Tutorials, Talks, Articles, News, Background Reading, etc. on Mahout](/community/books-tutorials-and-talks.html) - -[Issue Tracker](/developers/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](/community/mailing-lists.html) - -- links to our mailing lists, IRC channel and archived design and -algorithm discussions, maybe your questions was answered there already? - -[Version Control](/developers/version-control.html) - -- where we track our code. - -[Powered By Mahout](/community/powered-by-mahout.html) - -- who is using Mahout in production? - -[Professional Support](/community/professional-support.html) - -- who is offering professional support for Mahout? - -[Mahout and Google Summer of Code](/community/gsoc.html) - -- All you need to know about Mahout and GSoC. - - -[Glossary of commonly used terms and abbreviations](/community/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](/community/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/3a724deb/website/front/community/mailing-lists.md ---------------------------------------------------------------------- diff --git a/website/front/community/mailing-lists.md b/website/front/community/mailing-lists.md index c5c5400..c33baba 100644 --- a/website/front/community/mailing-lists.md +++ b/website/front/community/mailing-lists.md @@ -10,65 +10,38 @@ 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 +<div class="container-fluid"> + <div class="row"> + <div class="col-md-8"><div class="mahoutMailListBox1"> + <b>User</b> - 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. + </div></div> + <div class="col-md-2"><div class="mahoutMailListBox1"><a href="mailto:[email protected]";>Subscribe</a></div></div> + <div class="col-md-2"><div class="mahoutMailListBox1"><a href="mailto:[email protected]";>Un-Subscribe</a></div></div> + </div> + <div class="row"> + <div class="col-md-8"><div class="mahoutMailListBox2"> + <b>Developers</b> - 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. + </div></div> + <div class="col-md-2"><div class="mahoutMailListBox2"><a href="mailto:[email protected]";>Subscribe</a></div></div> + <div class="col-md-2"><div class="mahoutMailListBox2"><a href="mailto:[email protected]";>Un-Subscribe</a></div></div> + </div> + <div class="row"> + <div class="col-md-8"><div class="mahoutMailListBox1"><b>Commits</b></div></div> + <div class="col-md-2"><div class="mahoutMailListBox1"><a href="mailto:[email protected]";>Subscribe</a></div></div> + <div class="col-md-2"><div class="mahoutMailListBox1"><a href="mailto:[email protected]";>Un-Subscribe</a></div></div> + </div> + +</div> -<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. +* [New Pony Mail [email protected]](https://lists.apache.org/[email protected]) +* [New Pony Mail [email protected]](https://lists.apache.org/[email protected]) +* [Old Apache Mail Archives [email protected]](http://mail-archives.apache.org/mod_mbox/mahout-dev/) +* [Old Apache Mail Archives [email protected]](http://mail-archives.apache.org/mod_mbox/mahout-user/) http://git-wip-us.apache.org/repos/asf/mahout/blob/3a724deb/website/front/community/powered-by-mahout.md ---------------------------------------------------------------------- diff --git a/website/front/community/powered-by-mahout.md b/website/front/community/powered-by-mahout.md deleted file mode 100644 index da47301..0000000 --- a/website/front/community/powered-by-mahout.md +++ /dev/null @@ -1,129 +0,0 @@ ---- -layout: default -title: Powered By Mahout -theme: - name: mahout2 ---- - -# 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/3a724deb/website/front/community/professional-support.md ---------------------------------------------------------------------- diff --git a/website/front/community/professional-support.md b/website/front/community/professional-support.md deleted file mode 100644 index 3386579..0000000 --- a/website/front/community/professional-support.md +++ /dev/null @@ -1,39 +0,0 @@ ---- -layout: default -title: Professional Support -theme: - name: mahout2 ---- - -<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/3a724deb/website/front/developers/githubPRs.md ---------------------------------------------------------------------- diff --git a/website/front/developers/githubPRs.md b/website/front/developers/githubPRs.md index 5879729..c8d65f0 100644 --- a/website/front/developers/githubPRs.md +++ b/website/front/developers/githubPRs.md @@ -11,13 +11,13 @@ theme: ---------- -## how to create a PR (for contributers) +## How to Create a PR (for contributers) Read [[1]]. Pull requests are made to apache/mahout repository on Github. -## merging a PR and closing it (for committers). +## Merging a PR and Closing it (for committers). Remember that pull requests are equivalent to a remote branch with potentially a multitude of commits. In this case it is recommended to squash remote commit history to have one commit per issue, rather @@ -26,8 +26,8 @@ same time, it is recommended to use **squash commits**. Read [[2]] (merging locally). Merging pull requests are equivalent to merging contributor's branch: - git checkout master # switch to local master branch - git pull apache master # fast-forward to current remote HEAD + git checkout develop # switch to local master branch + git pull apache develop # fast-forward to current remote HEAD git pull --squash https://github.com/cuser/mahout cbranch # merge to master @@ -43,8 +43,6 @@ fast forward is possible, so you get chance to change things before committing. At this point resolve conflicts, if any, or ask contributor to rebase on top of master, if PR went out of sync. -Also run regular patch checks and change CHANGELOG. - Suppose everything is fine, you now can commit the squashed request git commit -a @@ -52,10 +50,14 @@ Suppose everything is fine, you now can commit the squashed request edit message to contain "MAHOUT-YYYY description **closes #ZZ**", where ZZ is the pull request number. Including "closes #ZZ" will close PR automatically. More information [[3]]. - push apache master + push apache develop (this will require credentials). +Note on `develop` branch: Minor patches, bug fixes, complete features, etc. may be merged to `develop`. Features that +are still under development should be pushed to a feature branch with reasonable name or better yet `mahout-xxxx` where +`xxxx` is the JIRA number. + Note on squashing: Since squash discards remote branch history, repeated PRs from the same remote branch are difficult for merging. The workflow implies that every new PR starts with a new rebased branch. This is more important for contributors to know, rather than for committers, because if new PR is not mergeable, github http://git-wip-us.apache.org/repos/asf/mahout/blob/3a724deb/website/front/developers/key-concepts.md ---------------------------------------------------------------------- diff --git a/website/front/developers/key-concepts.md b/website/front/developers/key-concepts.md new file mode 100644 index 0000000..9071bab --- /dev/null +++ b/website/front/developers/key-concepts.md @@ -0,0 +1,43 @@ +--- +layout: default +title: Key Concepts Overview +theme: + name: mahout2 +--- + + +Stub: +## Mahout-Samsara Mathematically Expressive Scala DSL + +High level over view of how user creates DRMs (which are actually wrappers around underlying bindings data structure) +How Samsara gives R-Like syntax to these DRMs with operations like `drmA.t %*% drmA`. How the spirit of this is to let +practitioners quickly develop their own distributed algorithms. + +## Distributed Bindings + +Here we'll talk a bit how the user can write distributed bindings for any engine they wish, how they must implement a few +linear algebra operations on the distributed engine in question. + +## Native Solvers + +How in JVM based distributed engines, computations happens at JVM on node, native solvers tell application how to dump +out of JVM and calculate natively, then load back into JVM for shipping. + + +## Linear Algebra Algorithms + +How algos like dssvd dspca dqr, etc make back bone of algos framework. + +## Reccomenders + +Mahout's long legacy as leader in Reccomenders in big data, and what is available today. + +## Distributed Statistics / Machine Learning Algos a.k.a. pre-canned algos. + +How we recognize that not everyone wants to re-invent K-means and linear regression so we are building up a collection of +common and essoteric algorithms that will come 'pre-canned' + +## Map Reduce + +How these are legacy but still exist. + http://git-wip-us.apache.org/repos/asf/mahout/blob/3a724deb/website/front/developers/reference.md ---------------------------------------------------------------------- diff --git a/website/front/developers/reference.md b/website/front/developers/reference.md deleted file mode 100644 index 911301d..0000000 --- a/website/front/developers/reference.md +++ /dev/null @@ -1,73 +0,0 @@ ---- -layout: default -title: Reference Reading -theme: - name: mahout2 ---- - -**note** tg: was this already in teh website and just lost or did dustin add it? - -# 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/3a724deb/website/front/developers/thirdparty-dependencies.md ---------------------------------------------------------------------- diff --git a/website/front/developers/thirdparty-dependencies.md b/website/front/developers/thirdparty-dependencies.md deleted file mode 100644 index 9a7b7ec..0000000 --- a/website/front/developers/thirdparty-dependencies.md +++ /dev/null @@ -1,30 +0,0 @@ ---- -layout: default -title: hirdparty Dependencies -theme: - name: mahout2 ---- - -# Adding Thirdparty Dependencies in Maven - -If you have a dependency on a third party artifact that is not in Maven, -you should: - - -* Ask the project to add it if at all possible. Most open source projects -want wider adoption, so this kind of request is often well received. -* If they won't add it, we may be able to add it to our Maven repo, -assuming it can be published at the ASF at all (no GPL code, for instance). - Please ask on the mailing list first. -* Assuming it can be, then you need to sign and deploy the artifacts, as -described below: - -*mvn gpg:sign-and-deploy-file -Durl=https://repository.apache.org/service/local/staging/deploy/maven2 -DrepositoryId=apache.releases.https -DgroupId=org.apache.mahout.foobar -DartifactId=foobar -Dversion=x.y -Dpackaging=jar -Dfile=foobar-x.y.jar* - -* Once it is deployed, go into [http://repository.apache.org/](http://repository.apache.org/) by using your SVN -credentials to login in -* Select Staging -* Find your repository artifacts -* Close them (this makes them publicly available, since you are closing the -staging repo) -* Promote them. This adds them to the public Maven repo. http://git-wip-us.apache.org/repos/asf/mahout/blob/3a724deb/website/front/index.md ---------------------------------------------------------------------- diff --git a/website/front/index.md b/website/front/index.md index 2c0841e..ab66336 100644 --- a/website/front/index.md +++ b/website/front/index.md @@ -5,13 +5,66 @@ theme: --- +<div class="container-fluid"> + <div class="row"> + <div class="col-md-8"> + <div class="row"> + <div class="col-s-12"> + <div class="mahoutBox1"> + <h4> Apache Mahout(TM) is a <b>distributed linear algebra framework</b> and <b>mathematically expressive Scala DSL</b> + designed to let mathematicians, statisticians, and data scientists quickly <i>implementent their own algorithms</i>. + Apache Spark is the reccomended out-of-the-box distributed back-end, <i>or can be extended to other distributed backends.</i></h4> + </div></div> + </div> <!-- row --> + <div class="row"> + <div class="col-xs-4"> + <div class="mahoutBox3"><b>Mathematically Expressive Scala DSL</b> + </div></div> + <div class="col-xs-4"> + <div class="mahoutBox2"><b>Support for Multiple Distributed Backends (including Apache Spark)</b> + </div></div> + <div class="col-xs-4"> + <div class="mahoutBox2"><b>Modular Native Solvers for CPU/GPU/CUDA Acceleration</b> + </div></div> + </div> <!-- row --> + </div> + <div class="col-md-4"> + <div class="mahoutBox2 col-md-11"> + <div class='jekyll-twitter-plugin'> + <a class="twitter-timeline" data-width="300" data-height="300" data-tweet-limit="4" data-chrome="nofooter" href="https://twitter.com/ApacheMahout";>Tweets by ApacheMahout</a> + <script async src="//platform.twitter.com/widgets.js" charset="utf-8"></script> + </div></div> + </div> + </div> +</div> -<div class="jumbotron"> -<h4> Apache Mahout(TM) is a <b>distributed linear algebra framework</b> and <b>mathematically expressive Scala DSL</b> - designed to let mathematicians, statisticians, and data scientists quickly <i>implementent their own algorithms</i>. - Apache Spark is the reccomended out-of-the-box distributed back-end, <i>or can be extended to other distributed backends.</i> +<!-- +<div class="container"> + <div class="row"> + <div class="col-9"> + <div class="mahoutBox1"> + <h4> Apache Mahout(TM) is a <b>distributed linear algebra framework</b> and <b>mathematically expressive Scala DSL</b> + designed to let mathematicians, statisticians, and data scientists quickly <i>implementent their own algorithms</i>. + Apache Spark is the reccomended out-of-the-box distributed back-end, <i>or can be extended to other distributed backends.</i></h4> + </div> + </div> <!-- col9 --> +<!-- +<div class="col-3"> + <div class="row"> + <div class="col-md-12 col-sm-12 col-xs-12 text-center"> + <div class='jekyll-twitter-plugin'><a class="twitter-timeline" data-width="500" data-tweet-limit="4" data-chrome="nofooter" href="https://twitter.com/ApacheMahout";>Tweets by ApacheMahout</a> + <script async src="//platform.twitter.com/widgets.js" charset="utf-8"></script></div> + </div> + <div class="col-md-12 col-sm-12 col-xs-12 text-center twitterBtn"> + <p style="text-align:center; margin-top: 32px; font-size: 12px; color: gray; font-weight: 200; font-style: italic; padding-bottom: 0;">See more tweets or</p> + <a href="https://twitter.com/ApacheMahout"; target="_blank" class="btn btn-primary btn-lg round" role="button">Follow Mahout on <i class="fa fa-twitter fa-lg" aria-hidden="true"></i></a> + </div> + </div> </div> +</div> +<div class="row"> +<!-- Jumbotron --> <!-- <div class="newMahout col-md-4 col-sm-4"> @@ -91,17 +144,5 @@ theme: </div> </div> </aside> ---> -<div class="row"></div> -<div class="container col-sm-6 col-md-12"> - <div class="row"> - <div class="col-md-12 col-sm-12 col-xs-12 text-center"> - <div class='jekyll-twitter-plugin'><a class="twitter-timeline" data-width="500" data-tweet-limit="4" data-chrome="nofooter" href="https://twitter.com/ApacheMahout";>Tweets by ApacheMahout</a> - <script async src="//platform.twitter.com/widgets.js" charset="utf-8"></script></div> - </div> - <div class="col-md-12 col-sm-12 col-xs-12 text-center twitterBtn"> - <p style="text-align:center; margin-top: 32px; font-size: 12px; color: gray; font-weight: 200; font-style: italic; padding-bottom: 0;">See more tweets or</p> - <a href="https://twitter.com/ApacheMahout"; target="_blank" class="btn btn-primary btn-lg round" role="button">Follow Mahout on <i class="fa fa-twitter fa-lg" aria-hidden="true"></i></a> - </div> - </div> - </div> +f--> +
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