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Data Science Happy Hour 20 | 19FEB2021
The Data Science Happy Hours keep getting happier!
Check it out and don't forget to register for future office hours: http://bit.ly/adsoh
Register for Sunday Sessions here: http://bit.ly/comet-ml-oh
If you want to interact with me multiple times a week, join Data Science Dream Job for 70% off: http://dsdj.co/artists70
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
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.
View all episodes
By Harpreet Sahota
4.9
5050 ratings
The Data Science Happy Hours keep getting happier!
Check it out and don't forget to register for future office hours: http://bit.ly/adsoh
Register for Sunday Sessions here: http://bit.ly/comet-ml-oh
If you want to interact with me multiple times a week, join Data Science Dream Job for 70% off: http://dsdj.co/artists70
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
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.
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