WEBVTT
Kind: captions
Language: en

00:00:00.000 --> 00:00:12.860 align:start position:0%
 
you

00:00:12.860 --> 00:00:12.870 align:start position:0%
 
 

00:00:12.870 --> 00:00:16.289 align:start position:0%
 
my<00:00:13.870><c> name</c><00:00:13.990><c> is</c><00:00:14.080><c> dipesh</c><00:00:14.380><c> i'm</c><00:00:15.160><c> working</c><00:00:15.640><c> for</c><00:00:15.849><c> Zynga</c>

00:00:16.289 --> 00:00:16.299 align:start position:0%
my name is dipesh i'm working for Zynga
 

00:00:16.299 --> 00:00:18.030 align:start position:0%
my name is dipesh i'm working for Zynga
right<00:00:16.480><c> now</c><00:00:16.689><c> and</c><00:00:16.960><c> I'm</c><00:00:17.439><c> working</c><00:00:17.770><c> there</c><00:00:17.890><c> as</c><00:00:18.010><c> a</c>

00:00:18.030 --> 00:00:18.040 align:start position:0%
right now and I'm working there as a
 

00:00:18.040 --> 00:00:21.000 align:start position:0%
right now and I'm working there as a
data<00:00:18.220><c> science</c><00:00:18.700><c> and</c><00:00:18.939><c> data</c><00:00:19.390><c> engineer</c><00:00:19.930><c> intern</c><00:00:20.260><c> so</c>

00:00:21.000 --> 00:00:21.010 align:start position:0%
data science and data engineer intern so
 

00:00:21.010 --> 00:00:23.400 align:start position:0%
data science and data engineer intern so
I<00:00:21.039><c> have</c><00:00:21.400><c> to</c><00:00:21.610><c> design</c><00:00:22.150><c> different</c><00:00:23.110><c> machine</c>

00:00:23.400 --> 00:00:23.410 align:start position:0%
I have to design different machine
 

00:00:23.410 --> 00:00:25.040 align:start position:0%
I have to design different machine
learning<00:00:23.740><c> models</c><00:00:23.920><c> based</c><00:00:24.430><c> on</c><00:00:24.610><c> different</c>

00:00:25.040 --> 00:00:25.050 align:start position:0%
learning models based on different
 

00:00:25.050 --> 00:00:34.950 align:start position:0%
learning models based on different
machine<00:00:26.050><c> learning</c><00:00:26.320><c> platforms</c><00:00:26.859><c> it's</c><00:00:27.340><c> fun</c><00:00:33.660><c> so</c><00:00:34.660><c> I</c>

00:00:34.950 --> 00:00:34.960 align:start position:0%
machine learning platforms it's fun so I
 

00:00:34.960 --> 00:00:38.100 align:start position:0%
machine learning platforms it's fun so I
started<00:00:35.440><c> my</c><00:00:35.650><c> internship</c><00:00:36.160><c> with</c><00:00:37.149><c> sky</c><00:00:37.600><c> mind</c><00:00:37.899><c> and</c>

00:00:38.100 --> 00:00:38.110 align:start position:0%
started my internship with sky mind and
 

00:00:38.110 --> 00:00:40.620 align:start position:0%
started my internship with sky mind and
then<00:00:38.739><c> sky</c><00:00:39.280><c> mine</c><00:00:39.489><c> is</c><00:00:39.730><c> deep</c><00:00:40.000><c> learning</c><00:00:40.149><c> for</c><00:00:40.450><c> your</c>

00:00:40.620 --> 00:00:40.630 align:start position:0%
then sky mine is deep learning for your
 

00:00:40.630 --> 00:00:43.740 align:start position:0%
then sky mine is deep learning for your
library<00:00:41.790><c> the</c><00:00:42.790><c> power</c><00:00:43.000><c> D</c><00:00:43.180><c> planning</c><00:00:43.450><c> for</c><00:00:43.630><c> your</c>

00:00:43.740 --> 00:00:43.750 align:start position:0%
library the power D planning for your
 

00:00:43.750 --> 00:00:47.880 align:start position:0%
library the power D planning for your
library<00:00:43.870><c> can</c><00:00:44.559><c> we</c><00:00:44.649><c> do</c><00:00:44.800><c> it</c><00:00:44.920><c> again</c><00:00:46.860><c> well</c><00:00:47.860><c> I</c>

00:00:47.880 --> 00:00:47.890 align:start position:0%
library can we do it again well I
 

00:00:47.890 --> 00:00:49.740 align:start position:0%
library can we do it again well I
started<00:00:48.309><c> working</c><00:00:48.730><c> on</c><00:00:48.910><c> Scala</c><00:00:49.210><c> with</c><00:00:49.540><c> my</c>

00:00:49.740 --> 00:00:49.750 align:start position:0%
started working on Scala with my
 

00:00:49.750 --> 00:00:52.490 align:start position:0%
started working on Scala with my
internship<00:00:50.530><c> at</c><00:00:50.680><c> deep</c><00:00:51.280><c> learning</c><00:00:51.430><c> forge</c><00:00:51.820><c> a</c>

00:00:52.490 --> 00:00:52.500 align:start position:0%
internship at deep learning forge a
 

00:00:52.500 --> 00:00:56.160 align:start position:0%
internship at deep learning forge a
powerhouse<00:00:53.500><c> sky</c><00:00:54.129><c> mind</c><00:00:54.370><c> and</c><00:00:54.579><c> I</c><00:00:55.510><c> also</c><00:00:55.809><c> worked</c>

00:00:56.160 --> 00:00:56.170 align:start position:0%
powerhouse sky mind and I also worked
 

00:00:56.170 --> 00:00:57.690 align:start position:0%
powerhouse sky mind and I also worked
with<00:00:56.260><c> data</c><00:00:56.530><c> breaks</c><00:00:56.770><c> during</c><00:00:56.920><c> my</c><00:00:57.190><c> master's</c><00:00:57.340><c> in</c>

00:00:57.690 --> 00:00:57.700 align:start position:0%
with data breaks during my master's in
 

00:00:57.700 --> 00:00:59.160 align:start position:0%
with data breaks during my master's in
data<00:00:57.850><c> science</c><00:00:58.120><c> so</c><00:00:58.539><c> clearly</c><00:00:58.809><c> when</c><00:00:59.020><c> you're</c>

00:00:59.160 --> 00:00:59.170 align:start position:0%
data science so clearly when you're
 

00:00:59.170 --> 00:01:00.660 align:start position:0%
data science so clearly when you're
thinking<00:00:59.500><c> about</c><00:00:59.559><c> Spock</c><00:01:00.010><c> you</c><00:01:00.190><c> have</c><00:01:00.219><c> to</c><00:01:00.489><c> think</c>

00:01:00.660 --> 00:01:00.670 align:start position:0%
thinking about Spock you have to think
 

00:01:00.670 --> 00:01:02.729 align:start position:0%
thinking about Spock you have to think
about<00:01:00.760><c> Scala</c><00:01:01.149><c> and</c><00:01:01.360><c> that's</c><00:01:02.110><c> how</c><00:01:02.230><c> I</c><00:01:02.260><c> started</c><00:01:02.410><c> my</c>

00:01:02.729 --> 00:01:02.739 align:start position:0%
about Scala and that's how I started my
 

00:01:02.739 --> 00:01:11.490 align:start position:0%
about Scala and that's how I started my
journey<00:01:02.890><c> my</c><00:01:09.420><c> ideal</c><00:01:10.420><c> stack</c><00:01:10.720><c> is</c><00:01:11.020><c> grace</c><00:01:11.289><c> fragua</c>

00:01:11.490 --> 00:01:11.500 align:start position:0%
journey my ideal stack is grace fragua
 

00:01:11.500 --> 00:01:14.850 align:start position:0%
journey my ideal stack is grace fragua
is<00:01:11.800><c> pancake</c><00:01:12.250><c> probably</c><00:01:13.259><c> the</c><00:01:14.259><c> actual</c><00:01:14.619><c> stack</c>

00:01:14.850 --> 00:01:14.860 align:start position:0%
is pancake probably the actual stack
 

00:01:14.860 --> 00:01:20.339 align:start position:0%
is pancake probably the actual stack
that<00:01:15.039><c> we</c><00:01:15.220><c> have</c><00:01:15.399><c> right</c><00:01:15.580><c> now</c><00:01:15.640><c> has</c><00:01:18.240><c> we</c><00:01:19.240><c> have</c><00:01:19.450><c> what</c>

00:01:20.339 --> 00:01:20.349 align:start position:0%
that we have right now has we have what
 

00:01:20.349 --> 00:01:21.839 align:start position:0%
that we have right now has we have what
you<00:01:20.470><c> got</c><00:01:20.619><c> at</c><00:01:20.740><c> a</c><00:01:20.770><c> set</c><00:01:21.069><c> and</c><00:01:21.250><c> we</c><00:01:21.399><c> have</c><00:01:21.550><c> spark</c>

00:01:21.839 --> 00:01:21.849 align:start position:0%
you got at a set and we have spark
 

00:01:21.849 --> 00:01:24.210 align:start position:0%
you got at a set and we have spark
ecosystem<00:01:22.509><c> and</c><00:01:22.690><c> then</c><00:01:23.349><c> we</c><00:01:23.530><c> are</c><00:01:23.619><c> upgrading</c><00:01:23.740><c> it</c>

00:01:24.210 --> 00:01:24.220 align:start position:0%
ecosystem and then we are upgrading it
 

00:01:24.220 --> 00:01:27.480 align:start position:0%
ecosystem and then we are upgrading it
to<00:01:24.250><c> different</c><00:01:24.869><c> of</c><00:01:25.869><c> streaming</c><00:01:26.800><c> platforms</c><00:01:27.429><c> like</c>

00:01:27.480 --> 00:01:27.490 align:start position:0%
to different of streaming platforms like
 

00:01:27.490 --> 00:01:29.880 align:start position:0%
to different of streaming platforms like
Kafka<00:01:27.940><c> and</c><00:01:28.209><c> we</c><00:01:28.780><c> are</c><00:01:28.840><c> hoping</c><00:01:29.170><c> to</c><00:01:29.229><c> migrate</c><00:01:29.709><c> to</c>

00:01:29.880 --> 00:01:29.890 align:start position:0%
Kafka and we are hoping to migrate to
 

00:01:29.890 --> 00:01:33.480 align:start position:0%
Kafka and we are hoping to migrate to
newer<00:01:30.190><c> and</c><00:01:30.459><c> newer</c><00:01:30.670><c> data</c><00:01:31.539><c> systems</c>

00:01:33.480 --> 00:01:33.490 align:start position:0%
newer and newer data systems
 

00:01:33.490 --> 00:01:40.050 align:start position:0%
newer and newer data systems
oh<00:01:37.829><c> I'm</c><00:01:38.829><c> really</c><00:01:39.399><c> interested</c><00:01:39.549><c> in</c><00:01:39.820><c> attending</c>

00:01:40.050 --> 00:01:40.060 align:start position:0%
oh I'm really interested in attending
 

00:01:40.060 --> 00:01:42.539 align:start position:0%
oh I'm really interested in attending
all<00:01:40.329><c> the</c><00:01:40.479><c> panels</c><00:01:40.840><c> it's</c><00:01:41.439><c> simply</c><00:01:41.979><c> amazing</c><00:01:42.159><c> to</c>

00:01:42.539 --> 00:01:42.549 align:start position:0%
all the panels it's simply amazing to
 

00:01:42.549 --> 00:01:57.420 align:start position:0%
all the panels it's simply amazing to
learn<00:01:42.729><c> from</c><00:01:42.909><c> experts</c><00:01:43.090><c> what</c><00:01:43.630><c> they</c><00:01:43.780><c> are</c><00:01:43.840><c> up</c><00:01:43.899><c> to</c>

00:01:57.420 --> 00:01:57.430 align:start position:0%
 
 

00:01:57.430 --> 00:01:59.490 align:start position:0%
 
you