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Apr 6, 2024
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Update 455-first-data-job.txt #140

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15 changes: 7 additions & 8 deletions transcripts/455-first-data-job.txt
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Expand Up @@ -468,7 +468,7 @@

00:18:05 What was the problem? I initialized the logger with the string info for the level rather than

00:18:11 the enumeration dot info, which was an integer based enum. So the logging statement would crash
00:18:11 the enumeration.info, which was an integer based enum. So the logging statement would crash

00:18:18 saying that I could not use less than or equal to between strings and ints. Crazy town. But with

Expand Down Expand Up @@ -582,7 +582,7 @@

00:22:52 kind of jobs you do? I think that's really important because it's easy to get focused in

00:22:58 on the FANG companies. I want to work for some super big tech company. I want to move to San
00:22:58 on the FAANG companies. I want to work for some super big tech company. I want to move to San

00:23:04 Francisco and like that, that, that, right. Like there's not just plenty of other jobs,

Expand All @@ -598,13 +598,13 @@

00:23:32 maybe more niche type of industries and companies might even be easier for a first job.

00:23:38 People seem to be really obsessed with, with the FANG. And I don't know if that's like a
00:23:38 People seem to be really obsessed with, with the FAANG. And I don't know if that's like a

00:23:42 societal thing or if it's just, those are the companies that we use a lot. And so we're excited

00:23:46 about them, but yeah, there's so many more data jobs outside of FANG than there are inside of
00:23:46 about them, but yeah, there's so many more data jobs outside of FAANG than there are inside of

00:23:51 FANG, even though there's, there's quite a bit inside of FANG. And oftentimes those roles can be
00:23:51 FAANG, even though there's, there's quite a bit inside of FAANG. And oftentimes those roles can be

00:23:57 much more interesting and you can do a lot bigger of an impact. When, when I was working at this

Expand Down Expand Up @@ -674,11 +674,11 @@

00:26:43 And then the other time, the other position I did there, we were doing a lot of auto ML

00:26:48 using PyCaret and letting it kind of decide what type of models to do. So.
00:26:48 using PyCharm and letting it kind of decide what type of models to do. So.

00:26:52 - Okay. The unsupervised learning type stuff, huh?

00:26:54 - It was awesome. It was really fun to, I love PyCaret because it's like, okay,
00:26:54 - It was awesome. It was really fun to, I love PyCharm because it's like, okay,

00:26:58 go make 25 models and tell me which one's the best. It's like, makes my job easy, I guess.

Expand Down Expand Up @@ -1473,4 +1473,3 @@
00:59:10 write some Python code.

00:59:12 [Music]