mjhirn

I have been working and thinking about data and ML models for many years and this is probably the most concise and lucid summary of a post NN philosophy I have heard so far. It also resonates with me. Thanks for sharing.

Unlike some of those top comments, I actually like your curation a lot. Prefer it to The Economist, New York Book Review, and the other sites ppl linked in the comments. Good job!

I know you have an RSS feed, and the crowd here probably is all for RSS, but I would love it if I could leave my email somewhere and get a notification when a new submit was posted.

I was thinking along those lines in the first half of my twenties. Now in the second half I feel lucky that I found a topic that I am going deep on and I am using that to go wide in some other connected areas.

In hindsight there was some time where I had to actively force myself to stick with one topic longer than usual to go deep. Once that hurdle is taken I have less of a problem now integrating adjacent topics.

I also agree with the advice that focusing on one topic improves professional success. Long-term is TBD though.

Quick question: What's the reason for making "Transform" part of the Feature Store definition. I've been evaluating a couple of feature stores (incl. Tecton and Feast - great job by the way willempienaar) and I'm wondering if that doesn't complicate things. Especially if you already have your own data processing pipes.

Ines Montani is the woman behind the awesome web design. I worked with her previously - she is amazing!

"Operation Transformation" = "a system that supports collaboration functionalities by separating the high-level transformation (or integration) control from the low-level transformation functions"

Source: OT's Wikipedia article

But I felt the same. Never heard of "Operation Transformation" before and both OT and its alias were equally opaque to me.

Hearing friends talking about flaking, I would say it is a very common theme. I would also think, that you may not want to meet up with that person, because either not in the same city, or because you may match with a lot of different people which also may change over time.

I also thought of it more like a self-validation thing, a source of more information, recommendations, etc. What you would get back may be an online conversation or a feed of relevant websites.

Good question! Could see that a conversation with that person may go very stale very quickly, but may have some other benefits?

- Great reading recommendations

- Great proof-of-competence like a 'badge' or 'degree' when hiring