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my<00:00:12.300><c> name</c><00:00:12.509><c> is</c><00:00:12.660><c> niyati</c><00:00:13.019><c> parmeshwar</c><00:00:13.799><c> I</c><00:00:14.130><c> work</c><00:00:14.880><c> as</c><00:00:15.150><c> a</c>

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my name is niyati parmeshwar I work as a
 

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my name is niyati parmeshwar I work as a
data<00:00:15.750><c> scientist</c><00:00:16.260><c> for</c><00:00:16.710><c> the</c><00:00:17.310><c> IBM</c><00:00:17.789><c> Watson</c><00:00:18.300><c> group</c>

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a<00:00:26.369><c> lot</c><00:00:26.910><c> comes</c><00:00:27.210><c> from</c><00:00:27.510><c> just</c><00:00:27.750><c> the</c><00:00:27.900><c> name</c><00:00:28.080><c> because</c><00:00:28.740><c> I</c>

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a lot comes from just the name because I
 

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a lot comes from just the name because I
work<00:00:29.519><c> as</c><00:00:29.670><c> a</c><00:00:29.699><c> data</c><00:00:29.939><c> scientist</c><00:00:30.420><c> and</c><00:00:30.689><c> this</c>

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work as a data scientist and this
 

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work as a data scientist and this
conference<00:00:32.610><c> data</c><00:00:33.000><c> by</c><00:00:33.149><c> the</c><00:00:33.210><c> bay</c><00:00:33.420><c> is</c><00:00:33.480><c> supposed</c>

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conference data by the bay is supposed
 

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conference data by the bay is supposed
to<00:00:34.110><c> bring</c><00:00:34.290><c> in</c><00:00:34.500><c> a</c><00:00:34.800><c> lot</c><00:00:35.430><c> of</c><00:00:35.489><c> data</c><00:00:36.300><c> scientists</c>

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to bring in a lot of data scientists
 

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to bring in a lot of data scientists
whose<00:00:37.260><c> primary</c><00:00:37.620><c> focus</c><00:00:38.610><c> and</c><00:00:38.820><c> the</c><00:00:39.180><c> focus</c><00:00:39.210><c> of</c><00:00:39.600><c> a</c>

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whose primary focus and the focus of a
 

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whose primary focus and the focus of a
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lot of talks here revolves around all
 

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lot of talks here revolves around all
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steps with data converting that data
 

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steps with data converting that data
into<00:00:46.230><c> information</c><00:00:46.430><c> right</c><00:00:47.430><c> from</c>

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into information right from
 

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into information right from
pre-processing<00:00:48.270><c> munging</c><00:00:48.960><c> and</c><00:00:49.260><c> then</c>

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pre-processing munging and then
 

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pre-processing munging and then
rendering<00:00:50.910><c> insights</c><00:00:51.300><c> out</c><00:00:51.570><c> of</c><00:00:51.719><c> that</c><00:00:51.840><c> data</c><00:00:52.050><c> so</c>

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rendering insights out of that data so
 

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rendering insights out of that data so
that's<00:00:53.460><c> why</c><00:00:53.610><c> it's</c><00:00:53.640><c> really</c><00:00:54.000><c> exciting</c><00:00:54.420><c> to</c><00:00:54.750><c> be</c>

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that's why it's really exciting to be
 

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that's why it's really exciting to be
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it's<00:01:03.890><c> exciting</c><00:01:04.460><c> because</c><00:01:04.879><c> it</c><00:01:05.420><c> kind</c><00:01:05.690><c> of</c><00:01:05.810><c> when</c>

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it's exciting because it kind of when
 

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it's exciting because it kind of when
you<00:01:06.860><c> get</c><00:01:07.040><c> really</c><00:01:07.460><c> noisy</c><00:01:08.440><c> clunky</c><00:01:09.440><c> data</c><00:01:09.970><c> you</c>

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you get really noisy clunky data you
 

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you get really noisy clunky data you
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kind of as the data scientist you kind
 

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kind of as the data scientist you kind
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of want to see what kind of structure
 

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of want to see what kind of structure
exists<00:01:15.110><c> in</c><00:01:15.260><c> that</c><00:01:15.530><c> data</c><00:01:15.710><c> so</c><00:01:15.979><c> that</c><00:01:16.010><c> you</c><00:01:16.250><c> can</c>

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exists in that data so that you can
 

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exists in that data so that you can
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proceed to put in probably a predictive
 

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proceed to put in probably a predictive
analytics<00:01:19.490><c> framework</c><00:01:19.670><c> or</c><00:01:20.119><c> a</c><00:01:20.360><c> recommendation</c>

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analytics framework or a recommendation
 

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analytics framework or a recommendation
engine<00:01:21.470><c> basically</c><00:01:21.890><c> find</c><00:01:22.250><c> out</c><00:01:22.400><c> what</c><00:01:22.610><c> that</c>

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engine basically find out what that
 

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engine basically find out what that
structure<00:01:23.330><c> is</c><00:01:23.509><c> so</c><00:01:23.720><c> it's</c><00:01:23.869><c> kind</c><00:01:24.110><c> of</c><00:01:24.170><c> a</c><00:01:24.259><c> challenge</c>

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structure is so it's kind of a challenge
 

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structure is so it's kind of a challenge
because<00:01:24.890><c> every</c><00:01:25.610><c> data</c><00:01:25.850><c> set</c><00:01:26.119><c> that</c><00:01:26.150><c> you</c><00:01:26.390><c> get</c><00:01:26.600><c> is</c>

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because every data set that you get is
 

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because every data set that you get is
obviously<00:01:27.380><c> not</c><00:01:27.800><c> the</c><00:01:27.979><c> same</c><00:01:28.190><c> and</c><00:01:28.430><c> that</c><00:01:28.460><c> kind</c><00:01:29.330><c> of</c>

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obviously not the same and that kind of
 

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obviously not the same and that kind of
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variety allows you to think of
 

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variety allows you to think of
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variations in terms of what you
 

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variations in terms of what you
potentially<00:01:34.340><c> could</c><00:01:34.520><c> do</c><00:01:34.700><c> with</c><00:01:34.910><c> that</c><00:01:34.940><c> data</c><00:01:35.210><c> and</c>

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potentially could do with that data and
 

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potentially could do with that data and
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how you can leverage it when you're
 

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how you can leverage it when you're
conceptualizing<00:01:37.670><c> your</c><00:01:38.300><c> algorithmic</c>

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conceptualizing your algorithmic
 

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conceptualizing your algorithmic
paradigm<00:01:39.320><c> or</c><00:01:39.470><c> framework</c>

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I<00:01:48.210><c> have</c><00:01:49.210><c> kind</c><00:01:49.510><c> of</c><00:01:49.710><c> in</c><00:01:50.710><c> my</c><00:01:50.860><c> talk</c><00:01:51.070><c> I'm</c><00:01:51.220><c> talking</c>

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I have kind of in my talk I'm talking
 

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I have kind of in my talk I'm talking
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about two projects that frameworks have
 

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about two projects that frameworks have
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built at our Watson and these frameworks
 

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built at our Watson and these frameworks
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while they can be used individually by
 

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while they can be used individually by
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themselves and still have utility
 

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themselves and still have utility
because<00:02:03.580><c> one</c><00:02:04.000><c> is</c><00:02:04.180><c> about</c><00:02:04.390><c> face</c><00:02:04.690><c> detection</c><00:02:04.870><c> in</c>

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because one is about face detection in
 

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because one is about face detection in
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belfries generation finger and the other
 

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belfries generation finger and the other
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works for automatic text summarization I
 

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works for automatic text summarization I
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also talked about how we can sync this
 

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also talked about how we can sync this
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to existing Watson services to
 

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to existing Watson services to
essentially<00:02:16.960><c> improve</c><00:02:17.950><c> the</c><00:02:18.910><c> way</c><00:02:19.060><c> that</c><00:02:19.090><c> the</c>

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essentially improve the way that the
 

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essentially improve the way that the
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service performs I want attendees of
 

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service performs I want attendees of
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course there are going to be people with
 

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course there are going to be people with
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a clear background in machine learning
 

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a clear background in machine learning
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who would have a sense of auto encoders
 

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who would have a sense of auto encoders
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recursive water encoders and the other
 

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recursive water encoders and the other
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things that I would be speaking of my
 

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things that I would be speaking of my
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talk but I'm hoping that even for
 

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talk but I'm hoping that even for
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someone who was not very familiar with
 

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someone who was not very familiar with
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machine learning I would be able to
 

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machine learning I would be able to
explain<00:02:38.320><c> to</c><00:02:39.130><c> them</c><00:02:39.370><c> from</c><00:02:39.880><c> a</c><00:02:40.150><c> high</c><00:02:40.330><c> level</c>

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explain to them from a high level
 

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explain to them from a high level
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perspective as to what this framework
 

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perspective as to what this framework
does<00:02:42.490><c> and</c><00:02:44.130><c> basically</c><00:02:45.130><c> the</c><00:02:45.340><c> potential</c><00:02:45.990><c> that</c>

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does and basically the potential that
 

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does and basically the potential that
exists<00:02:47.470><c> when</c><00:02:47.620><c> you</c><00:02:47.740><c> build</c><00:02:47.980><c> frameworks</c><00:02:48.430><c> like</c>

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exists when you build frameworks like
 

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exists when you build frameworks like
these<00:02:48.820><c> and</c><00:02:48.970><c> how</c><00:02:49.090><c> they're</c><00:02:49.270><c> easy</c><00:02:49.540><c> to</c><00:02:50.050><c> do</c><00:02:50.200><c> it</c><00:02:50.350><c> it's</c>

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these and how they're easy to do it it's
 

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these and how they're easy to do it it's
not<00:02:50.830><c> so</c><00:02:51.040><c> complicated</c>

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I'd<00:03:01.040><c> say</c><00:03:01.459><c> the</c><00:03:02.209><c> machine</c><00:03:02.450><c> learning</c><00:03:02.900><c> community</c>

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I'd say the machine learning community
 

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I'd say the machine learning community
in<00:03:03.560><c> the</c><00:03:03.680><c> data</c><00:03:03.860><c> science</c><00:03:04.159><c> community</c><00:03:04.610><c> as</c><00:03:04.760><c> a</c><00:03:04.790><c> whole</c>

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in the data science community as a whole
 

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in the data science community as a whole
is<00:03:05.299><c> very</c><00:03:05.569><c> very</c><00:03:05.750><c> active</c><00:03:06.260><c> right</c><00:03:06.680><c> now</c><00:03:06.739><c> so</c><00:03:08.439><c> if</c><00:03:09.439><c> you</c>

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is very very active right now so if you
 

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is very very active right now so if you
just<00:03:10.310><c> start</c><00:03:10.909><c> from</c><00:03:11.180><c> downloading</c><00:03:11.659><c> hacker</c><00:03:12.049><c> news</c>

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just start from downloading hacker news
 

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just start from downloading hacker news
one<00:03:13.069><c> or</c><00:03:13.549><c> two</c><00:03:13.970><c> out</c><00:03:14.150><c> of</c><00:03:14.180><c> the</c><00:03:14.480><c> five</c><00:03:14.629><c> articles</c><00:03:15.019><c> that</c>

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one or two out of the five articles that
 

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one or two out of the five articles that
get<00:03:15.670><c> published</c><00:03:16.670><c> every</c><00:03:17.000><c> day</c><00:03:17.180><c> would</c><00:03:17.390><c> be</c><00:03:17.569><c> around</c>

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get published every day would be around
 

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get published every day would be around
this<00:03:18.200><c> space</c><00:03:18.549><c> just</c><00:03:19.549><c> start</c><00:03:19.849><c> to</c><00:03:21.640><c> just</c><00:03:22.640><c> start</c><00:03:22.819><c> to</c>

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this space just start to just start to
 

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this space just start to just start to
actively<00:03:23.269><c> participate</c><00:03:23.480><c> and</c><00:03:24.140><c> that's</c><00:03:24.409><c> one</c>

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actively participate and that's one
 

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actively participate and that's one
space<00:03:25.159><c> Coursera</c><00:03:26.090><c> and</c><00:03:26.209><c> Udacity</c><00:03:26.299><c> have</c><00:03:27.049><c> some</c>

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space Coursera and Udacity have some
 

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space Coursera and Udacity have some
really<00:03:27.470><c> great</c><00:03:27.769><c> courses</c><00:03:28.670><c> in</c><00:03:29.180><c> the</c><00:03:29.480><c> space</c><00:03:29.720><c> of</c>

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really great courses in the space of
 

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really great courses in the space of
machine<00:03:30.200><c> learning</c><00:03:30.430><c> and</c><00:03:31.430><c> natural</c><00:03:31.940><c> language</c>

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machine learning and natural language
 

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machine learning and natural language
processing<00:03:32.290><c> gaggle</c><00:03:33.290><c> is</c><00:03:33.730><c> something</c><00:03:34.730><c> that</c>

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processing gaggle is something that
 

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processing gaggle is something that
every<00:03:35.299><c> mln</c><00:03:35.780><c> 2</c><00:03:35.930><c> z's</c><00:03:36.170><c> should</c><00:03:37.040><c> participate</c><00:03:37.370><c> in</c>

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every mln 2 z's should participate in
 

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every mln 2 z's should participate in
because<00:03:38.150><c> they</c><00:03:38.329><c> also</c><00:03:38.480><c> have</c><00:03:38.780><c> tutorials</c><00:03:39.139><c> and</c>

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because they also have tutorials and
 

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because they also have tutorials and
then<00:03:41.150><c> you</c><00:03:41.299><c> can</c><00:03:41.480><c> start</c><00:03:41.690><c> if</c><00:03:41.840><c> i</c><00:03:41.930><c> disobeyed</c><00:03:42.139><c> in</c>

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then you can start if i disobeyed in
 

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then you can start if i disobeyed in
competition<00:03:43.129><c> so</c><00:03:43.459><c> if</c><00:03:44.120><c> you</c><00:03:44.299><c> are</c><00:03:44.540><c> interested</c><00:03:44.569><c> in</c>

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competition so if you are interested in
 

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competition so if you are interested in
this<00:03:45.349><c> case</c><00:03:45.530><c> there's</c><00:03:45.829><c> a</c><00:03:45.920><c> lot</c><00:03:46.099><c> of</c><00:03:46.510><c> stuff</c><00:03:47.510><c> that's</c>

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this case there's a lot of stuff that's
 

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this case there's a lot of stuff that's
happening<00:03:48.049><c> around</c><00:03:48.170><c> that</c><00:03:48.470><c> you</c><00:03:48.590><c> can</c><00:03:48.739><c> easily</c>

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happening around that you can easily
 

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happening around that you can easily
parenting