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Most data scientists know git! Or, at the very least, how to follow a step-by-step git guide.

If notebooks are tracked anywhere at an org it's either where their code is stored (GitHub/GitLab), or in their managed notebook environment (Databricks/Hex)


interesting. that was not the case in 2019 when i did a bit of data science.

We've been around for a couple years now, wouldn't lie about the dev sign ups :)

Thanks for the feedback! Some of these questions are answered on our home page, but not all. Is anything unclear after looking at the home page?

Demo: https://app.gitnotebooks.com/GitNotebooks/demo/pull/1 Home Page: https://www.gitnotebooks.com/


A bit of feedback after downloading Znote:

- Couldn't execute the tutorial notebooks without first paying for a subscription

- Specifically surprised that executing a bash script locally is an "Advanced feature"

- I've "exceeded my limit 1/1" for deployed jobs, I'd love to see how/where this is deployed but I don't see a link. It's the default myapphtml job.

EDIT: Found the link to the deployed web app. Was confused because it has a column label of "Frequency"


Just a heads up: "Follow me on LinkedIn" doesn't link to your profile


My pride and joy: http://lipsislips.com


My girlfriend and I had fun with this, thanks for sharing!

As a sidenote, letsencrypt.com is free :)


That was unexpectedly fun :D Turns out: Lips _are_ lips!


This is a funny little game man. Thanks for sharing.


I like the idea of meeting others in my field. Any tips for finding this in SF? I'm building a dev tool


CBT is common and often covered by health insurance. I've been doing talk therapy for 3 years and I've found helpful for all kinds of things.

The most important (and hardest) part is finding a therapist you trust.


What do you use to collect telemetry data?


It's a mix of things, but the big one was ROS bag files for robots. So a lot of the conventional up-to-the-minute metrics workflows oriented around grafana/kibana don't really pan out when you're very interested in a five minute window that occurred three days ago, buried in a 1gb datafile.



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