Data Science Happy Hour 20 | 19FEB2021

The Data Science Happy Hours keep getting happier!

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Watch the episode on YouTube here: https://www.youtube.com/playlist?list=PLx-pFw_ty92wJoWzoO7WlfaM7iYB8_qjm

[00:03:19] The rise of new roles in data science

[00:04:10] What is it going to take, going forward, to start making money with machine learning and help companies on that road to maturity?

[00:06:54] What is an ML architect?

[00:09:13] Should a research oriented data scientist learn about architecture?

[00:12:41] Do you have to be a great software engineer to think like one?

[00:18:48] What is a feature store?

[00:20:57] The more I get into this data science/machine learning space…it's like the more I realized I don't know shit.

[00:23:22] Mikiko comes in with some awesome insight about feature sores

[00:28:48] When do I use a partition for a database?

[00:36:46] What are some other types of correlation?

[00:42:04] Thom with some wisdom.

[00:44:23] A question on web scraping (not people information, but product prices)

[00:55:17] The legality of web scraping

[00:58:15] How to understand how to help someone in the most effective way

[01:11:26] Figure out what the “ground truth” really is

[01:14:09] Why you need an emphasis on customer focus and how you can cultivate that mindset

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Some useful links from our discussion

00:23:14 Greg Coquillo
https://www.linkedin.com/posts/greg-coquillo_datascience-machinelearning-artificialintelligence-activity-6760977800963985408-ys5y

00:28:41 Joe Reis
https://www.youtube.com/watch?v=o4q_ljRkXqw

00:36:24 Mikiko Bazeley
https://learning.oreilly.com/library/view/designing-data-intensive-applications/9781491903063/ch06.html

00:37:55 Mikiko Bazeley
https://docs.snowflake.com/en/user-guide/tables-clustering-micropartitions.html)

00:42:50 Mark Freeman
https://drive.google.com/file/d/1qkURyDrEa4IkQRm0in26CNIpP84ws0Tf/view

00:43:51 Harpreet Sahota
https://realpython.com/numpy-scipy-pandas-correlation-python/

00:44:02 Mitul Patel
https://easystats.github.io/correlation/articles/types.html in R

00:47:07 Mark Freeman
https://towardsdatascience.com/rip-correlation-introducing-the-predictive-power-score-3d90808b9598

00:54:25 Mikiko Bazeley
https://realpython.com/courses/python-lambda-functions/

00:54:35 Mikiko Bazeley
https://learn.datacamp.com/courses/streaming-data-with-aws-kinesis-and-lambda

00:55:43 Mark Freeman
https://docs.aws.amazon.com/toolkit-for-eclipse/v1/user-guide/lambda-tutorial.html

00:56:54 Mark Freeman
https://docs.aws.amazon.com/lambda/latest/dg/welcome.html

00:58:14 Mikiko Bazeley
https://www.forbes.com/sites/emmawoollacott/2019/09/10/linkedin-data-scraping-ruled-legal/?sh=a0f2baa1b54b

00:58:20 Joe Reis
https://www.eff.org/deeplinks/2019/09/victory-ruling-hiq-v-linkedin-protects-scraping-public-data

01:06:32 Mark Freeman
https://www.datascience-pm.com/crisp-dm-2/

01:19:05 Mikiko Bazeley
https://www.linkedin.com/posts/crmercado_datascience-deeplearning-artificialintelligence-activity-6767800296333811712-Jf8r

01:24:20 Mark Freeman
https://voltagecontrol.com/blog/5-steps-of-the-design-thinking-process-a-step-by-step-guide/

01:24:45 Mark Freeman
https://steveblank.com/category/lean-launchpad/

01:27:27 Vikram Krishna Kotturu
https://join.slack.com/t/artofdatascienceloft/shared_invite/zt-dgzn8abm-ge_dKGxrc9Dsuhnly90WTw

01:27:45 Harpreet Sahota
https://join.slack.com/t/artofdatascienceloft/shared_invite/zt-dgzn8abm-ge_dKGxrc9Dsuhnly90WTw

Special Guests: Brandon Quach, PhD, Greg Coquillo, Mikiko Bazeley, and Vin Vashishta.