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I<00:00:22.760><c> have</c><00:00:23.480><c> a</c><00:00:23.510><c> distributed</c><00:00:24.350><c> systems</c><00:00:24.740><c> background</c>

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I have a distributed systems background
 

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I have a distributed systems background
that<00:00:25.550><c> I</c><00:00:25.580><c> transitioned</c><00:00:26.510><c> to</c><00:00:26.570><c> machine</c><00:00:26.990><c> learning</c>

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that I transitioned to machine learning
 

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that I transitioned to machine learning
the<00:00:28.310><c> most</c><00:00:28.970><c> interesting</c><00:00:29.450><c> part</c><00:00:29.660><c> for</c><00:00:29.840><c> me</c><00:00:29.960><c> was</c>

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the most interesting part for me was
 

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the most interesting part for me was
sharing<00:00:31.400><c> my</c><00:00:32.590><c> the</c><00:00:33.590><c> things</c><00:00:34.190><c> that</c><00:00:34.370><c> I</c><00:00:34.400><c> learned</c>

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sharing my the things that I learned
 

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sharing my the things that I learned
from<00:00:34.700><c> disparate</c><00:00:35.450><c> systems</c><00:00:35.750><c> that</c><00:00:36.320><c> actually</c>

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from disparate systems that actually
 

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from disparate systems that actually
work<00:00:36.890><c> in</c><00:00:37.250><c> machine</c><00:00:37.730><c> learning</c><00:00:38.059><c> that</c><00:00:38.090><c> was</c><00:00:38.420><c> quite</c>

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work in machine learning that was quite
 

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work in machine learning that was quite
interesting<00:00:38.960><c> to</c><00:00:39.830><c> share</c>

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the<00:00:49.989><c> two</c><00:00:50.860><c> talks</c><00:00:51.160><c> that</c><00:00:51.399><c> I</c><00:00:51.430><c> that</c><00:00:51.940><c> I</c><00:00:51.969><c> was</c><00:00:52.480><c> able</c><00:00:52.629><c> to</c>

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the two talks that I that I was able to
 

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the two talks that I that I was able to
attend<00:00:54.820><c> there</c><00:00:55.690><c> was</c><00:00:55.809><c> one</c><00:00:56.050><c> that</c><00:00:56.260><c> they</c><00:00:56.559><c> it's</c><00:00:57.309><c> a</c>

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attend there was one that they it's a
 

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attend there was one that they it's a
similar<00:00:57.790><c> talk</c><00:00:58.059><c> from</c><00:00:58.480><c> Sony</c><00:00:59.010><c> on</c><00:01:00.010><c> prediction</c>

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similar talk from Sony on prediction
 

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similar talk from Sony on prediction
services<00:01:01.120><c> and</c><00:01:01.390><c> the</c><00:01:02.110><c> other</c><00:01:02.230><c> one</c><00:01:02.410><c> was</c><00:01:02.649><c> there</c><00:01:03.370><c> was</c>

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services and the other one was there was
 

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services and the other one was there was
a<00:01:03.489><c> good</c><00:01:03.670><c> talk</c><00:01:03.850><c> on</c><00:01:04.030><c> rust</c><00:01:04.360><c> I</c><00:01:04.690><c> found</c><00:01:05.320><c> that</c><00:01:05.440><c> very</c>

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a good talk on rust I found that very
 

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a good talk on rust I found that very
interesting<00:01:14.670><c> that's</c><00:01:15.670><c> a</c><00:01:15.729><c> good</c><00:01:15.880><c> question</c><00:01:16.270><c> so</c>

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interesting that's a good question so
 

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interesting that's a good question so
machine<00:01:17.320><c> learning</c><00:01:17.619><c> is</c><00:01:17.830><c> quite</c><00:01:18.580><c> important</c><00:01:18.970><c> for</c>

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machine learning is quite important for
 

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machine learning is quite important for
a<00:01:19.420><c> company</c><00:01:19.899><c> like</c><00:01:19.930><c> Twitter</c><00:01:20.350><c> like</c><00:01:20.619><c> there</c><00:01:20.950><c> are</c><00:01:21.039><c> a</c>

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a company like Twitter like there are a
 

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a company like Twitter like there are a
lot<00:01:21.250><c> of</c><00:01:21.280><c> problems</c><00:01:21.820><c> that</c><00:01:22.000><c> we</c><00:01:22.149><c> can</c><00:01:22.330><c> do</c><00:01:22.500><c> we</c><00:01:23.500><c> can</c>

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lot of problems that we can do we can
 

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lot of problems that we can do we can
find<00:01:23.860><c> good</c><00:01:24.369><c> solution</c><00:01:24.970><c> or</c><00:01:25.090><c> very</c><00:01:25.570><c> better</c>

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find good solution or very better
 

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find good solution or very better
solution<00:01:26.320><c> using</c><00:01:26.679><c> using</c><00:01:27.310><c> machine</c><00:01:27.610><c> learning</c>

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solution using using machine learning
 

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solution using using machine learning
for<00:01:28.060><c> instance</c><00:01:28.360><c> how</c><00:01:28.509><c> do</c><00:01:28.570><c> you</c><00:01:28.690><c> rank</c><00:01:28.990><c> your</c>

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for instance how do you rank your
 

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for instance how do you rank your
timeline<00:01:30.280><c> what</c><00:01:30.520><c> tweet</c><00:01:30.970><c> should</c><00:01:31.539><c> be</c><00:01:31.660><c> shown</c><00:01:31.869><c> to</c>

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timeline what tweet should be shown to
 

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timeline what tweet should be shown to
certain<00:01:32.350><c> users</c><00:01:32.460><c> versus</c><00:01:33.460><c> other</c><00:01:33.640><c> users</c>

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certain users versus other users
 

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certain users versus other users
personalization<00:01:35.140><c> things</c><00:01:35.530><c> like</c><00:01:35.710><c> that</c><00:01:35.920><c> but</c>

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personalization things like that but
 

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personalization things like that but
there<00:01:36.729><c> are</c><00:01:36.850><c> also</c><00:01:37.060><c> other</c><00:01:37.330><c> things</c><00:01:37.420><c> that</c><00:01:37.899><c> that</c>

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there are also other things that that
 

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there are also other things that that
just<00:01:38.500><c> cannot</c><00:01:38.740><c> be</c><00:01:38.920><c> solved</c><00:01:39.340><c> at</c><00:01:39.429><c> any</c><00:01:39.580><c> other</c><00:01:39.729><c> way</c>

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just cannot be solved at any other way
 

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just cannot be solved at any other way
for<00:01:40.000><c> instance</c><00:01:41.190><c> dictating</c><00:01:42.190><c> obvious</c><00:01:42.729><c> or</c>

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for instance dictating obvious or
 

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for instance dictating obvious or
offensive<00:01:43.569><c> content</c><00:01:44.110><c> before</c><00:01:44.289><c> they</c><00:01:44.590><c> actually</c>

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offensive content before they actually
 

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offensive content before they actually
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create problems so being part of that
 

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create problems so being part of that
part<00:01:49.899><c> of</c><00:01:49.960><c> that</c><00:01:50.170><c> team</c><00:01:50.560><c> that</c><00:01:50.590><c> works</c><00:01:51.009><c> you</c><00:01:51.340><c> know</c>

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part of that team that works you know
 

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part of that team that works you know
helps<00:01:51.700><c> the</c><00:01:51.759><c> company</c><00:01:52.090><c> with</c><00:01:52.210><c> that</c><00:01:52.360><c> as</c><00:01:52.860><c> it's</c><00:01:53.860><c> been</c>

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helps the company with that as it's been
 

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helps the company with that as it's been
quite<00:01:54.310><c> interesting</c><00:01:54.340><c> for</c><00:01:54.880><c> me</c>

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I<00:02:03.820><c> get</c><00:02:04.820><c> to</c><00:02:05.140><c> you</c><00:02:06.140><c> know</c><00:02:06.229><c> since</c><00:02:06.710><c> I</c><00:02:06.860><c> moved</c><00:02:07.430><c> to</c>

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I get to you know since I moved to
 

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I get to you know since I moved to
machine<00:02:07.910><c> learning</c><00:02:08.090><c> with</c><00:02:08.570><c> the</c><00:02:08.660><c> distributed</c>

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machine learning with the distributed
 

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machine learning with the distributed
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systems background the next few years
 

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systems background the next few years
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I'm trying to learn a lot more on
 

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I'm trying to learn a lot more on
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machine learning and how I can apply
 

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machine learning and how I can apply
distributed<00:02:16.940><c> systems</c><00:02:17.620><c> principles</c><00:02:18.620><c> to</c><00:02:19.190><c> help</c>

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distributed systems principles to help
 

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distributed systems principles to help
improve<00:02:19.640><c> machine</c><00:02:20.000><c> learning</c><00:02:20.300><c> and</c><00:02:20.390><c> Twitter</c>

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I met a few good engineers while I was
 

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I met a few good engineers while I was
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here working on different ideas maybe
 

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here working on different ideas maybe
similar<00:02:37.000><c> problems</c><00:02:37.510><c> so</c><00:02:38.020><c> that</c><00:02:38.050><c> networking</c>

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similar problems so that networking
 

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similar problems so that networking
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aspect was quite interesting for me I
 

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aspect was quite interesting for me I
don't<00:02:42.430><c> have</c><00:02:42.850><c> anything</c><00:02:43.600><c> else</c><00:02:44.290><c> to</c><00:02:44.620><c> add</c>

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don't have anything else to add
 

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don't have anything else to add
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as far as improvement is concerned it
 

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as far as improvement is concerned it
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was quite quite well done
 

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was quite quite well done
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