4 Machine Learning Sessions at Structure:Data that Shouldn’t Be Missed

Here my short­list of the ses­sions at GigaOm Structure:Data that I am most excited about. The fact that they are clus­tered together at the begin­ning of Wednes­day, March 21 is purely coin­ci­den­tal. For the curi­ous, here is the full lineup of speak­ers.


STRUCTURING DECISIONS FROM UNSTRUCTURED DATA (8:40 AM), with Seth Grimes, Ron Avnur, Paul Spe­ciale and Staffan Truve.

The first long ses­sion of the con­fer­ence is about the gen­eral prob­lem induc­ing struc­ture in data. Athough the topic is quite broad, I hope to see Seth Grimes leads the dis­cuss to non-obvious and forward-thinking busi­ness appli­ca­tions, par­tic­u­larly of text mining.


MACHINE LEARNING’S IMPACT ON BUSINESS MODELS AND INDUSTRY STRUCTURES (9:10 AM), with George Gilbert, Cur­rie Boyle, Alexan­der Gray, Mok Oh, and Amar­nath Thombre.

Chris Dixon has writ­ten on the strug­gle for devel­op­ing effec­tive machine learn­ing busi­ness mod­els, argu­ing that ML is “too hot” to be mar­keted in a B2B set­ting. I would like to see speaker insight into ML ser­vices as a B2B busi­ness model, as opposed to inter­nal use of ML.


PUZZLING (12:05 PM), with Jeff Jonas.

I’ve been mean­ing to see Jeff Jonas for a while, ever since my friend Todd Huff­man (@odd) spoke glow­ingly of him. Jeff’s talk appears to extend an idea I’ve men­tioned in a recent talk: The next step in pre­dic­tive ana­lyt­ics is using joins on machine extracted data sets to extract higher-level information.


UNDERWRITING FOR THE UNDERBANKED THROUGH DATA MINING (3:00 PM), with Mathew Ingram and Dou­glass Merrill.

I’ve been inter­ested in the use of ML for assess­ing credit more accu­rately since read­ing Pando Daily’s tax­on­omy of lend­ing and learn­ing about star­tups in that space. Niche areas in lend­ing are grow­ing; con­sider, for exam­ple, in vitro loans, and the fact that credit scores were his­tor­i­cally dif­fi­cult to esti­mate in Brazil.


Dis­clo­sure: MetaOp­ti­mize is a media part­ner for GigaOm Structure:Data, which means that I get a free pass in exchang­ing for cov­er­ing the event. It also means you get a dis­count of 20% if you buy a ticket through this link.

  • http://twitter.com/turian/status/181130058851815424 Joseph Turian

    4 ML Ses­sions at Structure:Data that Shouldn’t Be Missed: http://t.co/g7AWs0pU Cit­ing @cdixon @odd @JeffJonas @SethGrimes @DataConf @mok_oh

  • http://twitter.com/atpassos_ml/status/181131059679870976 Alexan­dre Passos

    4 ML Ses­sions at Structure:Data that Shouldn’t Be Missed: http://t.co/g7AWs0pU Cit­ing @cdixon @odd @JeffJonas @SethGrimes @DataConf @mok_oh

  • http://twitter.com/sethgrimes/status/181147632230596608 Seth Grimes

    4 ML Ses­sions at Structure:Data that Shouldn’t Be Missed: http://t.co/g7AWs0pU Cit­ing @cdixon @odd @JeffJonas @SethGrimes @DataConf @mok_oh

  • http://twitter.com/marie_wallace/status/181153130661154816 Marie Wal­lace

    “@turian’s 4 ML Ses­sions at Structure:Data that Shouldn’t Be Missed, http://t.co/vD292BH9" @JeffJonas @SethGrimes Smart chappies!

  • http://twitter.com/yongsun/status/181319885484326912 yong­sun

    【share】 4 Machine Learn­ing Ses­sions at Structure:Data that Shouldn’t Be Missed: Here my… http://t.co/IVLNTJN3

  • http://twitter.com/nandodf/status/181382066372481025 Nando de Freitas

    4 Machine Learn­ing Ses­sions at Structure:Data that Shouldn’t Be Missed http://t.co/uaGyAS0N

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