Comet ML Office Hours 2 - 14FEB2021

Download Subscribe Transcript
00:00:00
/
01:21:35
RSS Feed Transcript Download (45.1 MB) Link with Timestamp

February 18th, 2021

1 hr 21 mins 35 secs

Season 9

Transcript

Link with Timestamp

Download MP3 (45.1 MB)

Your Host

About this Episode

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/

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

Connect with Ayodele

LinkedIn: https://www.linkedin.com/in/ayodeleodubela/

Twitter: https://twitter.com/DataSciBae

Check out her course on LinkedIn Learning: https://www.linkedin.com/learning/supervised-learning-essential-training/supervised-machine-learning-and-the-technology-boom

[00:00:09] Friendly banter between the hosts

[00:02:17] Did you learn anything new this week?

[00:02:56] What is MLOps?

[00:09:33] How MLOps is used in the finance industry

[00:11:04] Topics to brush up on if you’re looking to get into the finance space as a data scientist

[00:12:06] Resources for learning about GLMs

[00:15:00] The struggle of being a data scientist

[00:17:19] What to do when you feel like there is so much to learn and not enough time

[00:18:56] A few key things you should focus on when you’re breaking into the field

[00:22:01] The hardest part about SQL

[00:25:59] What skills do I try to showcase in my portfolio project?

[00:30:42] How am I supposed to gain business acumen when I don’t have a job?

[00:37:30] How do I get my profile noticed?

[00:38:52] Understand how to develop KPIs and how your model impacts them

[00:44:05] How would you split your time amongst different activities when doing a project?

[00:51:17] There are multiple algorithms to use, how do I choose?

[00:53:33] How to deal with these crazy job descriptions?

[01:01:09] How do I position myself as a valuable candidate for a job?

[01:07:19] Get people to do mock interviews with you

[01:07:48] Convincing business stakeholders of your results when they want to follow their gut

[01:15:17] Resources for picking up some nonobvious skills you need as a data scientist

[01:16:13] Template methodology for problem framing: https://www.comet.ml/reports-templates/project-scope-template/reports/template/project-scope

[01:18:14] Why you need to get as much hands on practice as you can

Episode Comments