thecellardoor

As someone who looks at GitHub accounts as a resume, I can tell you that improvement over time is amazing to see. Assuming it’s clear what’s most interesting or recent.

Seems like life goals

Does this support distributed nodes within the DAG or does it assume everything runs on a single node?

Does the Pseudocode example work for complicated functions too? Or is it limited to really basic stuff?

Cool ideas

There are so many options and this post tries to make some sense of the mess.

This seems really interesting to me, but wanted a critical second opinion. Seems like a much more elegant solution than the alternatives

This is oddly addictive. Just typing in stuff and see what colors it gives me :)

I think that by definition this is a tradeoff. Most times you talk to data scientists that want a fully automated end-2-end solution, that doesn't require they change anything about their current workflow, and that any future modifications to their workflow would be supported as well.

That is magical thinking. I prefer best of breed solutions that integrate nicely with other best of breed solutions every day. That way if a tool doesn't suit you tomorrow, you can relatively easily swap it out for something better

Congrats on the launch. To me this feels like DVC but with a slightly more convenient python API, and without the pipeline which might be really great. How are you organizing experiments though? Without Git it seems too easy to have experiments become unusable. And filtering according to accuracy is not really a solution..

Looks really interesting! How do you connect the data and models in my project to the code, so you know what to merge?

Also, any way to easily connect to an existing project on GitHub/GitLab?

There was this concept of objectives and counter objectives which was meant to combat Goodhart’s law. The idea was that you define what you want to measure and then define another metric which acts as regularization for the first. A good example is if you define a metric of WAU only, you might be motivated to bring in as many new users each week as possible. Setting a counter metric of retention makes you take into consideration that it’s important they stay.

I don’t remember who suggested this - I vaguely remember it was someone at a16z, but can’t find the original place I read it