The Apache Software Foundation Blog
Announcing BarCampApache Sydney, Australia
The Apache Software Foundation is happy to announce BarCampApache Sydney, Australia, the first ASF-backed event in the Southern Hemisphere!
Taking place 11th December 2010 at the University of Sydney's Darlington Centre, the BarCampApache "unconference" will be attendee-driven, facilitated by members of the Apache community and will focus on the “Apache Way” of developing software. The event is open to the public free of charge.
Those interested in using Apache products, how projects are developed within the ASF, open development techniques and best practices, Web 2.0-style data mashups, engaging with The Apache Software Foundation, and the general BarCamp experience are welcome to participate.
As the Apache community comprises thousands of committed individuals from around the world, there are always opportunities for attendees to help. And with all BarCamps, BarCampApache Sydney seeks active participation at all levels, including assisting with the physical set up to pre-event promotion to proposing discussion topics and blogging/tweeting during the event.
BarCampApache Sydney sponsors include the University of Sydney, Alfresco, IBM, and MaestroDev. Sponsorship opportunities are available. For more information, contact Brett Porter at brett AT apache DOT org, or Nick Burch at nick AT apache DOT org.
For more details about BarCampApache Sydney, its related activities, and to sign up, please visit the event wiki at http://barcamp.org/BarCampApacheSydney and follow the #barcampsydney tag.
We look forward to seeing you there!
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Posted at 04:21AM Nov 16, 2010 by Sally in General | |
Apache News Roundup from the ApacheCon Show Floor
The following newsworthy events took place during the course of ApacheCon North America 1-5 November:
1) Foundation Updates
Membership count: 330 (31 new Members; 52 emeritus)
Committer count: +2,500 (approximately 200 additional Committers over the past year)
The ASF is governed by the community it most directly serves -- the people collaborating within its projects. Apache Committers are developers who contribute (individuals who "commit" or "write" code, patches, or documentation) directly to the Apache code repository. Apache Members are Committers who have demonstrated merit in the Foundation’s growth, evolution, and progress, and have been nominated for and elected to be awarded ASF Membership by existing Members. ASF Members have the right to vote on community-related decisions; and and the ability propose an active user for Committership.
Sponsors: the ASF welcomed new Sponsors AMD and IBM at the Gold level, and Lucid Imagination at the Bronze level.
Java Community Process: the ASF's seat on the JCP Executive Committee was ratified on 2 November 2010.
2) Apache Projects
Apache Top-level Projects: 82 total; new Apache Projects added are Avro, Axis, Cassandra, Click, HBase, Hive, Karaf, Mahout, Nutch, Pivot, Shindig, Subversion, Tika, Traffic Server, UIMA.
Project updates include Apache Hive v0.6.0; Apache James Server 3.0-M1; Apache Jackrabbit v2.0.3 and v2.1.2; Apache Tomcat Connectors v1.2.31; and Apache Mahout v0.4.
Apache Incubator: 41 projects are currently under development. New to the Apache Incubator are: Alois, Clerezza, Deltacloud, Etch, Isis, libcloud, Lucene Connector Framework, Lucy, Nuvem, OODT, Whirr, and Zeta Components.
Apache Labs: 32 initiatives being sandboxed. Apache Labs projects are created to quickly explore technical viability without the necessity of community building.
BarCampApache: the ASF will be hosting its first event in Australia at the University of Sydney on 11 December 2010.
ApacheCon: the next North American conference will be in Vancouver, British Columbia, Canada, 7-11 November 2011.
For more information, contact Sally Khudairi, VP Marketing & Publicity at firstname.lastname@example.org.
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Posted at 09:41PM Nov 06, 2010 by Sally in General | |
The ASF asks: Have you met Apache Mahout?
Quick peek: Given the amount of data available in digital form to a huge amount of businesses today, Machine Learning is what helps you make sense of your data and provide better service to your customers:
- Given interaction logs of your web shop, Mahout helps come up with good recommendations for products customers might be interested in buying.
- When faced with an ever increasing stream of news articles Mahout is what helps you to reduce that information load to a manageable amount of groups of topically related articles.
Apache Mahout provides stable, industry ready implementations of machine learning algorithms that help make more out of your product. The project combines support for efficient standalone deployments with the possibility of scaling to a distributed Apache Hadoop cluster thus making it easy to scale with your business needs.
- Clustering, that is grouping items only based on their similarity;
- Classification, that is assigning items to pre-defined categories;
- Recommendation, that is identifying items a user might like based on his behaviour;
- Frequent Itemset Mining, that is identifying items that usually appear together e.g. in a customer purchase
- a permissive open source license supporting almost any business use-case you can think of;
- a very active community responding to user requests and helping analyse your specific data problems;
- a production ready implementation of algorithms covering most of the sophisticated data analysis jobs you would want to run on your data while still being open and easy to adjust to your specific needs.
- Model refactoring and CLI changes to improve integration and consistency
- New ClusterEvaluator and CDbwClusterEvaluator offer new ways to evaluate clustering effectiveness
- New VectorModelClassifier allows any set of clusters to be used for classification
- RecommenderJob has been evolved to a fully distributed item-based recommender
- More algorithms supported like Spectral Clustering and MinHash Clustering (still experimental), HMM based sequence classification from GSoC (currently as sequential version only and still experimental), new type of NB classifier, and feature reduction options for existing one, new Sequential logistic regression training framework, new SGD classifier
- New vector encoding framework for high speed vectorization without a pre-built dictionary
- Promoted several pieces of old Colt framework to tested status (QR decomposition, in particular)
- Distributed Lanczos SVD implementation
- Many, many small fixes, improvements, refactorings and cleanup
Posted at 01:59PM Nov 03, 2010 by Sally in General | |