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i'm<00:00:11.690><c> martin</c><00:00:12.690><c> fowler</c><00:00:12.870><c> the</c><00:00:13.320><c> founder</c><00:00:13.740><c> and</c><00:00:13.769><c> CEO</c><00:00:14.070><c> of</c>

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i'm martin fowler the founder and CEO of
 

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i'm martin fowler the founder and CEO of
corn<00:00:14.610><c> TX</c><00:00:21.830><c> the</c><00:00:22.830><c> great</c><00:00:23.039><c> audience</c><00:00:23.340><c> here</c><00:00:23.970><c> so</c><00:00:24.689><c> many</c>

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corn TX the great audience here so many
 

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corn TX the great audience here so many
of<00:00:25.619><c> the</c><00:00:26.010><c> valleys</c><00:00:26.880><c> best</c><00:00:27.240><c> data</c><00:00:27.599><c> scientists</c>

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of the valleys best data scientists
 

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of the valleys best data scientists
participate<00:00:29.010><c> in</c><00:00:29.160><c> the</c><00:00:29.279><c> conference</c><00:00:29.519><c> and</c><00:00:29.939><c> that's</c>

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participate in the conference and that's
 

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participate in the conference and that's
the<00:00:30.810><c> most</c><00:00:30.960><c> exciting</c><00:00:31.109><c> part</c><00:00:31.560><c> of</c><00:00:31.679><c> it</c><00:00:31.830><c> for</c><00:00:32.070><c> me</c><00:00:36.590><c> well</c>

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the most exciting part of it for me well
 

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the most exciting part of it for me well
it<00:00:37.739><c> has</c><00:00:37.920><c> so</c><00:00:38.100><c> many</c><00:00:38.160><c> applications</c><00:00:38.850><c> already</c><00:00:39.270><c> and</c>

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it has so many applications already and
 

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it has so many applications already and
it<00:00:40.649><c> becomes</c><00:00:41.430><c> more</c><00:00:41.670><c> and</c><00:00:41.760><c> more</c><00:00:41.850><c> important</c><00:00:42.390><c> in</c>

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it becomes more and more important in
 

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it becomes more and more important in
many<00:00:42.989><c> aspects</c><00:00:43.500><c> of</c><00:00:43.770><c> the</c><00:00:44.129><c> economy</c><00:00:44.399><c> so</c><00:00:44.850><c> there</c><00:00:45.030><c> is</c>

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many aspects of the economy so there is
 

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many aspects of the economy so there is
nowadays<00:00:46.160><c> almost</c><00:00:47.160><c> no</c><00:00:47.579><c> business</c><00:00:48.030><c> can</c><00:00:48.270><c> operate</c>

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nowadays almost no business can operate
 

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nowadays almost no business can operate
without<00:00:48.809><c> data</c><00:00:49.230><c> so</c><00:00:50.160><c> yeah</c><00:00:50.579><c> I</c><00:00:50.610><c> think</c><00:00:51.000><c> that</c><00:00:51.149><c> what</c>

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without data so yeah I think that what
 

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without data so yeah I think that what
makes<00:00:51.539><c> it</c><00:00:51.750><c> very</c><00:00:52.199><c> important</c><00:00:52.680><c> and</c><00:00:52.770><c> very</c>

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makes it very important and very
 

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makes it very important and very
exciting

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yeah<00:01:03.679><c> well</c><00:01:03.979><c> I</c><00:01:04.159><c> have</c><00:01:04.610><c> a</c><00:01:04.640><c> quantitative</c><00:01:05.269><c> finance</c>

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yeah well I have a quantitative finance
 

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yeah well I have a quantitative finance
background<00:01:05.750><c> so</c><00:01:06.170><c> the</c><00:01:06.320><c> main</c><00:01:06.470><c> inside</c><00:01:06.830><c> was</c><00:01:07.070><c> I</c>

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background so the main inside was I
 

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background so the main inside was I
wanted<00:01:08.479><c> to</c><00:01:08.570><c> show</c><00:01:08.720><c> them</c><00:01:08.869><c> that</c><00:01:09.140><c> machine</c>

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wanted to show them that machine
 

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wanted to show them that machine
learning<00:01:10.399><c> and</c><00:01:10.610><c> data</c><00:01:10.810><c> science</c><00:01:11.810><c> can</c><00:01:12.020><c> be</c><00:01:12.049><c> applied</c>

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learning and data science can be applied
 

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learning and data science can be applied
on<00:01:12.500><c> financial</c><00:01:13.220><c> data</c><00:01:13.399><c> as</c><00:01:13.610><c> well</c><00:01:13.729><c> and</c><00:01:14.320><c> can</c><00:01:15.320><c> be</c>

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on financial data as well and can be
 

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on financial data as well and can be
applied<00:01:15.590><c> in</c><00:01:15.799><c> a</c><00:01:15.860><c> very</c><00:01:16.039><c> successful</c><00:01:16.250><c> way</c>

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yeah<00:01:27.200><c> well</c><00:01:27.409><c> as</c><00:01:27.649><c> science</c><00:01:28.100><c> and</c><00:01:28.219><c> engineering</c>

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yeah well as science and engineering
 

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yeah well as science and engineering
degree<00:01:28.880><c> doesn't</c><00:01:29.180><c> hurt</c><00:01:29.360><c> but</c><00:01:30.880><c> basically</c><00:01:31.880><c> it's</c>

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degree doesn't hurt but basically it's
 

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degree doesn't hurt but basically it's
practice<00:01:34.149><c> to</c><00:01:35.149><c> become</c><00:01:35.240><c> or</c><00:01:35.780><c> two</c><00:01:36.020><c> to</c><00:01:36.140><c> get</c>

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practice to become or two to get
 

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practice to become or two to get
excellent<00:01:36.619><c> that's</c><00:01:36.950><c> something</c><00:01:37.520><c> you</c><00:01:37.670><c> always</c>

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excellent that's something you always
 

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excellent that's something you always
need<00:01:38.240><c> to</c><00:01:38.360><c> practice</c><00:01:38.780><c> a</c><00:01:38.990><c> lot</c><00:01:39.670><c> real</c><00:01:40.670><c> a</c><00:01:40.700><c> lot</c><00:01:40.970><c> so</c><00:01:41.240><c> we</c>

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need to practice a lot real a lot so we
 

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need to practice a lot real a lot so we
get<00:01:42.020><c> your</c><00:01:42.170><c> hands</c><00:01:42.350><c> dirty</c><00:01:42.470><c> and</c><00:01:42.970><c> write</c><00:01:43.970><c> codes</c>

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get your hands dirty and write codes
 

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get your hands dirty and write codes
predict<00:01:44.990><c> I'm</c><00:01:45.170><c> serious</c><00:01:45.530><c> work</c><00:01:45.799><c> with</c><00:01:45.950><c> data</c>

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predict I'm serious work with data
 

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predict I'm serious work with data
that's<00:01:46.759><c> the</c><00:01:46.939><c> only</c><00:01:47.149><c> way</c>