Recent Changes

Tuesday, October 10

  1. page Home edited ... Before posting jobs to the list, please check our Job Posting Policy. Next Meeting: ... 10…
    ...
    Before posting jobs to the list, please check our Job Posting Policy.
    Next Meeting:
    ...
    10th - Adam Russell, "Deep Learning in Perl""
    Real-world Artificial Intelligence in perl details

    Github Continuous Integration for Perl CPAN module" -- Live implementation demo!!
    details
    < ROOM
    ...
    Nov 14th - TBD, quite likely postponed Adam Russell, "Deep Learning in Perl"
    Real-world Artificial Intelligence in perl

    Parking alert.
    The full schedule and history can be found on our Calendar.
    (view changes)
    11:53 am
  2. page Calendar edited Would you like to present for Boston.pm? See our Presenter's Guide Current meeting ... 10th - …
    Would you like to present for Boston.pm? See our Presenter's Guide
    Current meeting
    ...
    10th - Adam Russell "Deep Learning in Perl"Github Continuous Integration for Perl CPAN modules
    Last minute Subject Change

    LIVE Speaker ! ROOM Change: E51-372
    DeepWe're sorry to report that due to circumstances beyond the speaker's control, Adam won't be able to make it tonight for his talk on "Deep Learning with AI::MXNet: Navigating implementation issues {Neural_network.png} Neural Network
    This
    in Perl." We are tentatively rescheduling that talk for our November meeting (update to follow).
    Instead tonight we
    will cover lessons learned frombe having a recent experience in getting a deep learning projected started, with little prior experience in AI. All code will use the Perl MXNet API and guide the audience through developing a simple model, which is then builtmini-hackathon on to perform more complex tasks.
    Artificial Intelligence (AI) has for a long time captured
    the popular imagination. Results from academia and industry have finally started to deliver on some of the long hoped for results: self driving cars, automated medical diagnoses, and written and verbal language processing. These areas are showing advancesConfig::Std CPAN module that were once simply products of fiction writers. The current wave of AI enthusiasm mayBoston.pm maintains. We'll be attributed to what is called Deep Learning which isoffering a convenient label for relatively new techniqueslive demonstration of setting up continuous integration (CI) using neural networks. The possibilityTravis CI and Appveyor, two hosted CI tools made freely available for increased automation across virtually every industry has resulted in the spinning up of many new startup companies,open source projects on Github. Join us as well as new projects within existing enterprises, resulting inwe stumble through the need to develop the skills necessary to pursue this new area.
    While not the language of production, Perl is used to develop algorithms
    process and demonstrate concepts before they receive fuller treatment. Deep Learning practitioners often begin their deep learning work, correctly,learn from our mistakes.
    Perl has had Test::Harness for decades,
    with a reviewCPANTS providing distributed Continuous Integration testing of the literature and research into the fundamentals. Projects then often start confidently with high hopes, built on that conceptual understanding, only to quickly get bogged down in unforeseen, but critically important, issues of implementation. Using Perl, and MXNet, asReleased CP {http://s3itch.paperplanes.de/Fullscreen-13-2-20120827-214248.png} Github - Travis-CI integration illo from Travic-CI blogAN module distributions for a rapid prototyping tool allows uncovering the promise ofdecade or more. Thank you CPANTS volunteers for creating a new algorithm without getting mired in implementation details.
    About the speaker
    Adam Russell is a software engineer with OptumLabs' Center
    distributed cloud for Applied Data Science (CADS). CADSus :-). Now GitHub is taskedoffering similar capabilities to all the other FLOSS communities via free integration with developing prototype applications which implement recent advances in algorithmsfreemium cloud Continuous Integration tools Travis-CI (for Linux) and technologyAppveyor (for Windows). Since we have CPANTS for release, we can use Travis-ci&Appveyor to address issues of importance to Optum business interests. Most recenttest our DEV branch after checkin. They'll even test Pull Requests before merge! Any Github FLOSS project can use these, but Perl CPAN projects can make use easily since we already have been focused on Deep Learning. Adam has a PhD in Computer Science fromregression testing culture, we won't need to write the University of Massachusetts Lowell, his academic interests involve Computational Geometry and Data Visualization and these explorations, much like the work described in this talk, are all Perl driven. He also teaches, on an adjunct basis,tests, just enable them.
    Join us to help me make "easily" true or laugh
    at Wentworth Institute of Technology in Boston.my hubris to say Easy before I try doing it :-)
    NOTE: Parking Alert. Recent changes in MIT Parking Dept web pages (parking , visitors, public ) no longer allow un-permitted parking after-hours.
    (This is a natural response to several other East Campus parking lots being eaten by new building sites for campus expansion.)
    ...
    Unconfirmed Room
    2018
    Next
    November 14th Subject TBD but quite possibly October original postponed as follows
    Adam Russell : Deep Learning with Perl and AI::MXNet: Navigating implementation issues {Neural_network.png} Neural Network
    This talk will cover lessons learned from a recent experience in getting a deep learning projected started, with little prior experience in AI. All code will use the Perl MXNet API and guide the audience through developing a simple model, which is then built on to perform more complex tasks.
    Artificial Intelligence (AI) has for a long time captured the popular imagination. Results from academia and industry have finally started to deliver on some of the long hoped for results: self driving cars, automated medical diagnoses, and written and verbal language processing. These areas are showing advances that were once simply products of fiction writers. The current wave of AI enthusiasm may be attributed to what is called Deep Learning which is a convenient label for relatively new techniques using neural networks. The possibility for increased automation across virtually every industry has resulted in the spinning up of many new startup companies, as well as new projects within existing enterprises, resulting in the need to develop the skills necessary to pursue this new area.
    While not the language of production, Perl is used to develop algorithms and demonstrate concepts before they receive fuller treatment. Deep Learning practitioners often begin their deep learning work, correctly, with a review of the literature and research into the fundamentals. Projects then often start confidently with high hopes, built on that conceptual understanding, only to quickly get bogged down in unforeseen, but critically important, issues of implementation. Using Perl, and MXNet, as a rapid prototyping tool allows uncovering the promise of a new algorithm without getting mired in implementation details.
    About the speaker
    Adam Russell is a software engineer with OptumLabs' Center for Applied Data Science (CADS). CADS is tasked with developing prototype applications which implement recent advances in algorithms and technology to address issues of importance to Optum business interests. Most recent projects have been focused on Deep Learning. Adam has a PhD in Computer Science from the University of Massachusetts Lowell, his academic interests involve Computational Geometry and Data Visualization and these explorations, much like the work described in this talk, are all Perl driven. He also teaches, on an adjunct basis, at Wentworth Institute of Technology in Boston.

    Past
    Tues, Sep 12th - Damian Conway, "Three Little Words" (or "Why I Love Perl") (recorded at The 2017 Perl Conference)
    (view changes)
    11:51 am

Friday, October 6

  1. page Calendar edited ... This talk will cover lessons learned from a recent experience in getting a deep learning proje…
    ...
    This talk will cover lessons learned from a recent experience in getting a deep learning projected started, with little prior experience in AI. All code will use the Perl MXNet API and guide the audience through developing a simple model, which is then built on to perform more complex tasks.
    Artificial Intelligence (AI) has for a long time captured the popular imagination. Results from academia and industry have finally started to deliver on some of the long hoped for results: self driving cars, automated medical diagnoses, and written and verbal language processing. These areas are showing advances that were once simply products of fiction writers. The current wave of AI enthusiasm may be attributed to what is called Deep Learning which is a convenient label for relatively new techniques using neural networks. The possibility for increased automation across virtually every industry has resulted in the spinning up of many new startup companies, as well as new projects within existing enterprises, resulting in the need to develop the skills necessary to pursue this new area.
    ...
    of implementation. Using Perl, and MXNet, as a rapid prototyping tool allows uncovering the promise of a new algorithm without getting mired in implementation details.
    About the speaker
    Adam Russell is a software engineer with OptumLabs' Center for Applied Data Science (CADS). CADS is tasked with developing prototype applications which implement recent advances in algorithms and technology to address issues of importance to Optum business interests. Most recent projects have been focused on Deep Learning. Adam has a PhD in Computer Science from the University of Massachusetts Lowell, his academic interests involve Computational Geometry and Data Visualization and these explorations, much like the work described in this talk, are all Perl driven. He also teaches, on an adjunct basis, at Wentworth Institute of Technology in Boston.
    (view changes)
    8:21 pm
  2. page Calendar edited ... Next Meeting - Tuesday, October 10th - Adam Russell "Deep Learning in Perl" LIVE Sp…
    ...
    Next Meeting - Tuesday, October 10th - Adam Russell "Deep Learning in Perl"
    LIVE Speaker ! ROOM Change: E51-372
    ...
    implementation issues {Neural_network.png} Neural Network
    This talk will cover lessons learned from a recent experience in getting a deep learning projected started, with little prior experience in AI. All code will use the Perl MXNet API and guide the audience through developing a simple model, which is then built on to perform more complex tasks.
    Artificial Intelligence (AI) has for a long time captured the popular imagination. Results from academia and industry have finally started to deliver on some of the long hoped for results: self driving cars, automated medical diagnoses, and written and verbal language processing. These areas are showing advances that were once simply products of fiction writers. The current wave of AI enthusiasm may be attributed to what is called Deep Learning which is a convenient label for relatively new techniques using neural networks. The possibility for increased automation across virtually every industry has resulted in the spinning up of many new startup companies, as well as new projects within existing enterprises, resulting in the need to develop the skills necessary to pursue this new area.
    (view changes)
    7:46 pm
  3. 7:44 pm
  4. page Calendar edited ... This talk will cover lessons learned from a recent experience in getting a deep learning proje…
    ...
    This talk will cover lessons learned from a recent experience in getting a deep learning projected started, with little prior experience in AI. All code will use the Perl MXNet API and guide the audience through developing a simple model, which is then built on to perform more complex tasks.
    Artificial Intelligence (AI) has for a long time captured the popular imagination. Results from academia and industry have finally started to deliver on some of the long hoped for results: self driving cars, automated medical diagnoses, and written and verbal language processing. These areas are showing advances that were once simply products of fiction writers. The current wave of AI enthusiasm may be attributed to what is called Deep Learning which is a convenient label for relatively new techniques using neural networks. The possibility for increased automation across virtually every industry has resulted in the spinning up of many new startup companies, as well as new projects within existing enterprises, resulting in the need to develop the skills necessary to pursue this new area.
    ...
    of implementation. Using Perl, and MXNet, as a rapid prototyping tool allows uncovering the promise of a new algorithm without getting mired in implementation details.
    About the speaker
    Adam Russell is a software engineer with OptumLabs' Center for Applied Data Science (CADS). CADS is tasked with developing prototype applications which implement recent advances in algorithms and technology to address issues of importance to Optum business interests. Most recent projects have been focused on Deep Learning. Adam has a PhD in Computer Science from the University of Massachusetts Lowell, his academic interests involve Computational Geometry and Data Visualization and these explorations, much like the work described in this talk, are all Perl driven. He also teaches, on an adjunct basis, at Wentworth Institute of Technology in Boston.
    (view changes)
    12:28 pm
  5. page Calendar edited ... LIVE Speaker ! ROOM Change: E51-372 Deep Learning with AI::MXNet: Navigating implementation i…
    ...
    LIVE Speaker ! ROOM Change: E51-372
    Deep Learning with AI::MXNet: Navigating implementation issues
    ...
    a simple modelmodel, which is
    ...

    Artificial Intelligence (AI) has for
    ...
    verbal language processingprocessing. These areas are showing advances that werewere once simply
    ...
    new startup companiescompanies, as well
    ...
    new area.
    Deep

    While not the language of production, Perl is used to develop algorithms and demonstrate concepts before they receive fuller treatment. Deep
    Learning practitioners
    ...
    with high hopeshopes, built on that conceptual understandingunderstanding, only to
    ...
    of implementation.
    Adam
    Using Perl, and MXNet, as a rapid prototyping tool allows uncovering the promise of a new algorithm without getting mired in implementation details.
    About the speaker
    Adam
    Russell is
    ...
    Deep Learning. While not the language of production, Perl is used to develop algorithms and demonstrate concepts before they receive fuller treatment. Adam has
    NOTE: Parking Alert. Recent changes in MIT Parking Dept web pages (parking , visitors, public ) no longer allow un-permitted parking after-hours.
    (This is a natural response to several other East Campus parking lots being eaten by new building sites for campus expansion.)
    (view changes)
    12:28 pm

Thursday, October 5

  1. page Home edited ... Before posting jobs to the list, please check our Job Posting Policy. Next Meeting: ... Me…
    ...
    Before posting jobs to the list, please check our Job Posting Policy.
    Next Meeting:
    ...
    Meeting - Tues, Sept 12th 7.30Tuesday, October 10th - The Perl Conference 2017 Review: Damian Conway TPC keynote "Three Little Words"
    More technical than that sounds, because Damian!
    Adam Russell, "Deep Learning in Perl""
    Real-world Artificial Intelligence in perl
    details <
    ...
    - Tuesday, Oct 10th - Adam Russell (live) "Deep Learning in Perl"Nov 14th
    Parking alert.
    The full schedule and history can be found on our Calendar.
    (view changes)
    10:03 pm
  2. page Calendar edited Would you like to present for Boston.pm? See our Presenter's Guide Current meeting Tues, Sep 12t…
    Would you like to present for Boston.pm? See our Presenter's Guide
    Current meeting
    Tues, Sep 12thNext Meeting - Damian Conway, "Three Little Words" (or "Why I Love Perl") (recorded at The 2017 Perl Conference)
    ROOM
    Tuesday, October 10th - Adam Russell "Deep Learning in Perl"
    LIVE Speaker ! ROOM
    Change: E51-372
    Damian Conway, known for his rapid-paced, wide-ranging, tour-de-force presentations, was

    Deep Learning with AI::MXNet: Navigating implementation issues
    This talk will cover lessons learned from a recent experience in getting a deep learning projected started, with little prior experience in AI. All code will use
    the keynote presenter at The Perl Conference, 2017 (formerly known as YAPC::NA). In his keynote he tells "a tale of madness, obsession,MXNet API and coding extremity," describing what it tookguide the audience through developing a simple model which is then built on to bring 3 keywordsperform more complex tasks.
    Artificial Intelligence has for a long time captured the popular imagination. Results
    from Perl 6academia and industry have finally started to Perl 5. A community effort that took three yearsdeliver on some of the long hoped for results: self driving cars, automated medical diagnoses, and 2.8 million lineswritten and verbal language processing are showing advances that were once simply products of code. Thisfiction writers. The current wave of AI enthusiasm may be attributed to what is called Deep Learning which is a more extreme exampleconvenient label for relatively new techniques using neural networks. The possibility for increased automation across virtually every industry has resulted in the spinning up of what some developers are going through to bring Perl 6 functionality to Perl 5.
    We will watch his recorded keynote and discuss among ourselves.
    Even if you are
    many new startup companies as well as new projects within existing enterprises, resulting in the need to Perl and don't follow alldevelop the technical details, Damian's highly entertaining presentations areskills necessary to pursue this new area.
    Deep Learning practitioners often begin their deep learning work, correctly, with
    a must see. (Plus, afterreview of the talk when we discuss it, we'll happily answer any questions.)
    About
    literature and research into the speaker
    {http://damian.conway.org/damian.jpg} Damian Conway
    fundamentals. Projects then often start confidently with high hopes built on that conceptual understanding only to quickly get bogged down in unforeseen, but critically important, issues of implementation.
    Adam Russell
    is an author or co-authora software engineer with OptumLabs' Center for Applied Data Science (CADS). CADS is tasked with developing prototype applications which implement recent advances in algorithms and technology to address issues of numerousimportance to Optum business interests. Most recent projects have been focused on Deep Learning. While not the language of production, Perl books,is used to develop algorithms and demonstrate concepts before they receive fuller treatment. Adam has a widely sought-after speakerPhD in Computer Science from the University of Massachusetts Lowell, his academic interests involve Computational Geometry and trainer.Data Visualization and these explorations, much like the work described in this talk, are all Perl driven. He also teaches, on an adjunct basis, at Wentworth Institute of Technology in Boston.
    NOTE: Parking Alert. Recent changes in MIT Parking Dept web pages (parking , visitors, public ) no longer allow un-permitted parking after-hours.
    (This is a natural response to several other East Campus parking lots being eaten by new building sites for campus expansion.)
    ...
    meters (late hours!)hours! and several blocks lost to construction), free spaces on Memorial Drive (allow time for circling), and paid
    Come by Train, Bus, Bicycle, or Foot if you can!
    (Parking at MBTA Garages are convenient to T and not overpriced, unlike most in-town garages.)
    ...
    RSVP for count encouraged but not required, to bill.n1vux@gmail.com or Boston-PM list, by 4pm Tuesday.
    (NOTE: Fall 2017: we're moving back to the squarer room 372 (first door after the partition), not the wider 376 (second door) that we had the last several years)
    Next Meeting - Tuesday, October 10th - Adam Russell "Deep Learning in Perl"
    LIVE Speaker !

    Future - Summer/Fall reservations
    *If you have a demo or talk idea, please, when would you like to present? Doesn't need to fill the full time.*
    ...
    CONFIRMED DATES.
    Room E51-372 reserved 6:30p - 10:00p (setup time!)
    Tues, Sep 12th
    Tues, Oct 10th

    Tues, Nov 14th
    Tues, Dec 12th , 2017
    ...
    2018
    Past
    Tues, Sep 12th - Damian Conway, "Three Little Words" (or "Why I Love Perl") (recorded at The 2017 Perl Conference)
    ROOM Change: E51-372
    Damian Conway, known for his rapid-paced, wide-ranging, tour-de-force presentations, was the keynote presenter at The Perl Conference, 2017 (formerly known as YAPC::NA). In his keynote he tells "a tale of madness, obsession, and coding extremity," describing what it took to bring 3 keywords from Perl 6 to Perl 5. A community effort that took three years and 2.8 million lines of code. This is a more extreme example of what some developers are going through to bring Perl 6 functionality to Perl 5.
    We will watch his recorded keynote and discuss among ourselves.
    Even if you are new to Perl and don't follow all the technical details, Damian's highly entertaining presentations are a must see. (Plus, after the talk when we discuss it, we'll happily answer any questions.)
    About the speaker
    {http://damian.conway.org/damian.jpg} Damian Conway is an author or co-author of numerous Perl books, and a widely sought-after speaker and trainer.

    August, 2017 - no meeting
    July 11th, 2017 The Perl Conference 2017 Review : Lightning Talk Dim Sum ( from TPC / YAPC::NA)
    (view changes)
    10:01 pm

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