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-pFwty92wJoWzoO7WlfaM7iYB8qjm
[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/sharedinvite/zt-dgzn8abm-gedKGxrc9Dsuhnly90WTw
01:27:45 Harpreet Sahota
https://join.slack.com/t/artofdatascienceloft/sharedinvite/zt-dgzn8abm-gedKGxrc9Dsuhnly90WTw
Special Guests: Brandon Quach, PhD, Greg Coquillo, Mikiko Bazeley, and Vin Vashishta.