Comet ML Office Hours 15 | 23MAY2021

Checkout the episode recap here: https://www.comet.ml/site/comet-office-hours-recap-for-may-23rd-and-may-30th/

Comet provides a self-hosted and cloud-based meta machine learning platform allowing data scientists and teams to track, compare, explain and optimize experiments and models.

Backed by thousands of users and multiple Fortune 100 companies, Comet provides insights and data to build better, more accurate AI models while improving productivity, collaboration and visibility across teams.

Register for future sessions here: http://bit.ly/comet-ml-oh

Checkout Comet ML by visiting: https://www.comet.ml/

Checkout the latest FREE e-book from Comet - Building Effective Machine Learning Teams: https://bit.ly/3bWrJ0O

Or on Twitter: https://twitter.com/CometML

On YouTube: https://www.youtube.com/channel/UCmN63HKvfXSCS-UwVwmK8Hw

Vote in the data community content creators awards! http://bit.ly/data-creators-awards

Check it out and don't forget to register for Friday Happy Hour sessions: http://bit.ly/adsoh

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

Checkout the interview I had with the Super Data Science Podcast: https://www.superdatascience.com/podcast/landing-your-data-science-dream-job

[00:01:08] How to deal with the confusion you face while learning new things

[00:04:09] Dealing with failed data science projects

[00:06:58] How do you go about making sure you collect the right kind of data in the first place?

[00:09:29] Start with three questions

[00:11:59] The balance between learning technical stuff and learning how to solve actual problems

[00:15:28] How are you overcoming learning struggles?

[00:18:07] Learning vs doing

[00:21:58] When the data doesn’t support much predictive power

[00:28:04] Everyone will become a data scientist, eventually

[00:30:38] The importance of domain knowledge

[00:35:03] Define failure up front

[00:37:56] Is low code the end of data science as we know it?

[00:42:19] Reproducibility

[00:48:25] Adam with some controversy

[01:02:36] How do you do personal inventory on your skills?