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From Seetharam Venkatesh <venkat...@innerzeal.com>
Subject Re: [VOTE] Accept PredictionIO into the Apache Incubator
Date Tue, 24 May 2016 17:50:08 GMT
+1 (binding)

All the best,
Venkatesh

On Tue, May 24, 2016 at 7:15 AM Ralph Goers <ralph.goers@dslextreme.com>
wrote:

> +1 (binding)
>
> Ralph
>
> > On May 24, 2016, at 3:44 AM, John D. Ament <johndament@apache.org>
> wrote:
> >
> > +1
> >
> > On Mon, May 23, 2016 at 6:23 PM Andrew Purtell <apurtell@apache.org>
> wrote:
> >
> >> Since discussion on the matter of PredictionIO has died down, I would
> like
> >> to call a VOTE
> >> on accepting PredictionIO into the Apache Incubator.
> >>
> >> Proposal: https://wiki.apache.org/incubator/PredictionIO
> >>
> >> ​[ ] +1 Accept PredictionIO into the Apache Incubator
> >> [ ] +0 Abstain
> >> [ ] -1 Do not accept PredictionIO into the Apache Incubator, because ...
> >>
> >> This vote will be open for at least 72 hours.
> >>
> >> My vote is +1 (binding)
> >>
> >> --
> >>
> >> PredictionIO Proposal
> >>
> >> Abstract
> >>
> >> PredictionIO is an open source Machine Learning Server built on top of
> >> state-of-the-art open source stack, that enables developers to manage
> and
> >> deploy production-ready predictive services for various kinds of machine
> >> learning tasks.
> >>
> >> Proposal
> >>
> >> The PredictionIO platform consists of the following components:
> >>
> >>   * PredictionIO framework - provides the machine learning stack for
> >>     building, evaluating and deploying engines with machine learning
> >>     algorithms. It uses Apache Spark for processing.
> >>
> >>   * Event Server - the machine learning analytics layer for unifying
> >> events
> >>     from multiple platforms. It can use Apache HBase or any JDBC
> backends
> >>     as its data store.
> >>
> >> The PredictionIO community also maintains a Template Gallery, a place to
> >> publish and download (free or proprietary) engine templates for
> different
> >> types of machine learning applications, and is a complemental part of
> the
> >> project. At this point we exclude the Template Gallery from the
> proposal,
> >> as it has a separate set of contributors and we’re not familiar with an
> >> Apache approved mechanism to maintain such a gallery.
> >>
> >> Background
> >>
> >> PredictionIO was started with a mission to democratize and bring machine
> >> learning to the masses.
> >>
> >> Machine learning has traditionally been a luxury for big companies like
> >> Google, Facebook, and Netflix. There are ML libraries and tools lying
> >> around the internet but the effort of putting them all together as a
> >> production-ready infrastructure is a very resource-intensive task that
> is
> >> remotely reachable by individuals or small businesses.
> >>
> >> PredictionIO is a production-ready, full stack machine learning system
> that
> >> allows organizations of any scale to quickly deploy machine learning
> >> capabilities. It comes with official and community-contributed machine
> >> learning engine templates that are easy to customize.
> >>
> >> Rationale
> >>
> >> As usage and number of contributors to PredictionIO has grown bigger and
> >> more diverse, we have sought for an independent framework for the
> project
> >> to keep thriving. We believe the Apache foundation is a great fit.
> Joining
> >> Apache would ensure that tried and true processes and procedures are in
> >> place for the growing number of organizations interested in contributing
> >> to PredictionIO. PredictionIO is also a good fit for the Apache
> foundation.
> >> PredictionIO was built on top of several Apache projects (HBase, Spark,
> >> Hadoop). We are familiar with the Apache process and believe that the
> >> democratic and meritocratic nature of the foundation aligns with the
> >> project goals.
> >>
> >> Initial Goals
> >>
> >> The initial milestones will be to move the existing codebase to Apache
> and
> >> integrate with the Apache development process. Once this is
> accomplished,
> >> we plan for incremental development and releases that follow the Apache
> >> guidelines, as well as growing our developer and user communities.
> >>
> >> Current Status
> >>
> >> PredictionIO has undergone nine minor releases and many patches.
> >> PredictionIO is being used in production by Salesforce.com as well as
> many
> >> other organizations and apps. The PredictionIO codebase is currently
> >> hosted at GitHub, which will form the basis of the Apache git
> repository.
> >>
> >> Meritocracy
> >>
> >> We plan to invest in supporting a meritocracy. We will discuss the
> >> requirements in an open forum. We intend to invite additional developers
> >> to participate. We will encourage and monitor community participation so
> >> that privileges can be extended to those that contribute.
> >>
> >> Community
> >>
> >> Acceptance into the Apache foundation would bolster the already strong
> >> user and developer community around PredictionIO. That community
> includes
> >> many contributors from various other companies, and an active mailing
> list
> >> composed of hundreds of users.
> >>
> >> Core Developers
> >>
> >> The core developers of our project are listed in our contributors and
> >> initial PPMC below. Though many are employed at Salesforce.com, there
> are
> >> also engineers from ActionML, and independent developers.
> >>
> >> Alignment
> >>
> >> The ASF is the natural choice to host the PredictionIO project as its
> goal
> >> is democratizing Machine Learning by making it more easily accessible to
> >> every user/developer. PredictionIO is built on top of several top level
> >> Apache projects as outlined above.
> >>
> >> Known Risks
> >>
> >> Orphaned Products
> >>
> >> PredictionIO has a solid and growing community. It is deployed on
> >> production environments by companies of all sizes to run various kinds
> of
> >> predictive engines.
> >>
> >> In addition to the community contribution to PredictionIO framework, the
> >> community is also actively contributing new engines to the Template
> >> Gallery as well as SDKs and documentation for the project. Salesforce is
> >> committed to utilize and advance the PredictionIO code base and support
> >> its user community.
> >>
> >> Inexperience with Open Source
> >>
> >> PredictionIO has existed as a healthy open source project for almost two
> >> years and is the most starred Scala project on GitHub. All of the
> proposed
> >> committers have contributed to ASF and Linux Foundation open source
> >> projects. Several current committers on Apache projects and Apache
> Members
> >> are involved in this proposal and intend to provide mentorship.
> >>
> >> Homogeneous Developers
> >>
> >> The initial list of committers includes developers from several
> >> institutions, including Salesforce, ActionML, Channel4, USC as well as
> >> unaffiliated developers.
> >>
> >> Reliance on Salaried Developers
> >>
> >> Like most open source projects, PredictionIO receives substantial
> support
> >> from salaried developers. PredictionIO development is partially
> supported
> >> by Salesforce.com, but there are many contributors from various other
> >> companies, and an active mailing list composed of hundreds of users. We
> >> will continue our efforts to ensure stewardship of the project to be
> >> independent of salaried developers by meritocratically promoting those
> >> contributors to committers.
> >>
> >> Relationships with Other Apache Product
> >>
> >> PredictionIO relies heavily on top level Apache projects such as Apache
> >> Spark, HBase and Hadoop. However it brings a distinguished
> functionality,
> >> rather than just an abstraction - Machine Learning in a plug-and-play
> >> fashion.
> >>
> >> Compared to Apache Mahout, which focuses on the development of a wide
> >> variety of algorithms, PredictionIO offers a platform to manage the
> whole
> >> machine learning workflow, including data collection, data preparation,
> >> modeling, deployment and management of predictive services in production
> >> environments.
> >>
> >> An Excessive Fascination with the Apache Brand
> >>
> >> PredictionIO is already a widely known open source project. This
> proposal
> >> is not for the purpose of generating publicity. Rather, the primary
> >> benefits to joining Apache are those outlined in the Rationale section.
> >>
> >> Documentation
> >>
> >> PredictionIO boasts rich and live documentation, included in the code
> repo
> >> (docs/manual directory), is built with Middleman, and publicly hosted at
> >> https://docs.prediction.io
> >>
> >> Initial Source and Intellectual Property Submission Plan
> >>
> >> Currently, the PredictionIO codebase is distributed under the Apache 2.0
> >> License and hosted on GitHub:
> https://github.com/PredictionIO/PredictionIO
> >>
> >> External Dependencies
> >>
> >> PredictionIO has the following external dependencies:
> >> * Apache Hadoop 2.4.0 (optional, required only if YARN and HDFS are
> >> needed)
> >> * Apache Spark 1.3.0 for Hadoop 2.4
> >> * Java SE Development Kit 8
> >> * and one of the following sets:
> >>   * PostgreSQL 9.1
> >> or
> >>   * MySQL 5.1
> >> or
> >>   * Apache HBase 0.98.6
> >>   * Elasticsearch 1.4.0
> >>
> >> Upon acceptance to the incubator, we would begin a thorough analysis of
> >> all transitive dependencies to verify this information and introduce
> >> license checking into the build and release process by integrating with
> >> Apache RAT.
> >>
> >> Cryptography
> >>
> >> PredictionIO does not include cryptographic code. We utilize standard
> >> JCE and JSSE APIs provided by the Java Runtime Environment.
> >>
> >> Required Resources
> >>
> >> We request that following resources be created for the project to use
> >>
> >> Mailing lists
> >>
> >>  predictionio-private@incubator.apache.org (with moderated
> subscriptions)
> >>  predictionio-dev
> >>  predictionio-user
> >>  predictionio-commits
> >>
> >>  We will migrate the existing PredictionIO mailing lists.
> >>
> >> Git repository
> >>
> >>  The PredictionIO team would like to use Git for source control, due to
> >> our
> >>  current use of GitHub.
> >>
> >>  git://git.apache.org/incubator-predictionio
> >>
> >> Documentation
> >>
> >>  https://predictionio.incubator.apache.org/docs/
> >>
> >> JIRA instance
> >>
> >>  PredictionIO currently uses the GitHub issue tracking system associated
> >>  with its repository:
> https://github.com/PredictionIO/PredictionIO/issues
> >> .
> >>  We will migrate to Apache JIRA.
> >>
> >>  JIRA PREDICTIONIO
> >>  https://issues.apache.org/jira/browse/PREDICTIONIO
> >>
> >> Other Resources
> >>
> >>  TravisCI for builds and test running.
> >>
> >>  PredictionIO's documentation, included in the code repo (docs/manual
> >>  directory), is built with Middleman and publicly hosted at
> >>  https://docs.prediction.io
> >>
> >>  A blog to drive adoption and excitement at https://blog.prediction.io
> >>
> >> Initial Committers
> >>
> >>  Pat Ferrell
> >>  Tamas Jambor
> >>  Justin Yip
> >>  Xusen Yin
> >>  Lee Moon Soo
> >>  Donald Szeto
> >>  Kenneth Chan
> >>  Tom Chan
> >>  Simon Chan
> >>  Marco Vivero
> >>  Matthew Tovbin
> >>  Yevgeny Khodorkovsky
> >>  Felipe Oliveira
> >>  Vitaly Gordon
> >>  Alex Merritt
> >>
> >> Affiliations
> >>
> >>  Pat Ferrell - ActionML
> >>  Tamas Jambor - Channel4
> >>  Justin Yip - independent
> >>  Xusen Yin - USC
> >>  Lee Moon Soo - NFLabs
> >>  Donald Szeto - Salesforce
> >>  Kenneth Chan - Salesforce
> >>  Tom Chan - Salesforce
> >>  Simon Chan - Salesforce
> >>  Marco Vivero - Salesforce
> >>  Matthew Tovbin - Salesforce
> >>  Yevgeny Khodorkovsky - Salesforce
> >>  Felipe Oliveira - Salesforce
> >>  Vitaly Gordon - Salesforce
> >>  Alex Merritt - ActionML
> >>
> >> Sponsors
> >>
> >> Champion
> >>
> >>  Andrew Purtell <apurtell at apache dot org>
> >>
> >> Nominated Mentors
> >>
> >>  Andrew Purtell <apurtell at apache dot org>
> >>  James Taylor <jtaylor at apache dot org>
> >>  Lars Hofhansl <larsh at apache dot org>
> >>  Suneel Marthi <smarthi at apache dot org>
> >>  Xiangrui Meng <meng at apache dot org>
> >>  Luciano Resende <lresende at apache dot org>
> >>
> >> Sponsoring Entity
> >>
> >>  Apache Incubator PMC
> >>
> >>
> >> --
> >> Best regards,
> >>
> >>   - Andy
> >>
> >> Problems worthy of attack prove their worth by hitting back. - Piet Hein
> >> (via Tom White)
> >>
>
>
>
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