boringds

I'd like to understand why, this doesn't sound obvious to me? Unhealthy overweight people, I can picture it, but otherwise? An athlete at 240 lbs might not see any benefit whatsoever for instance. In other cases I can also picture people gaining weight feeling much better under the right circumstances.

All in one weight in itself doesn't mean much in isolation. That's why you have people with a high BMI that are healthier than people with a "normal" one.

Absolutely. I wasn't taking a jab at your comment, just adding my experience. Thanks for sharing your point of view!

I'd like to add that while you are right for engineering, for certain analytics roles communication would be the decisive factor I'd consider (granted of course the candidate knows how to use SQL and got decent scripting skills). The reason is most of our job as analytics engineers is communication and translating stakeholders business problems.

I just started on the same medication after seeing a psychiatrist. We are experimenting on dosage. However it's frustrating, first month on 18 mg was almost better than the 27 mg I take right now, even though 18 mg in the end did nothing anymore. How did you find your optimal dosage?

My partner reports massive improvements (no fidgetting, calmness, less impulsive) but I still feel .... the same and sometimes worse when it comes to fatigue and work, even though I sleep well.

Good to note it's not impossible to be in a calorie deficit and not lose weight. Lipedema for instance makes it impossible to lose fat on the legs and arms. Hard to get a diagnostic for it too. Other than that your comment is right, you can also not lose weight when doing IF, it's all about calories in calories out.

FWIW and for others reading this. If you experience reflux regularly, go get checked. I had an undiagnosed H Pilory infection for years (can lead to cancer). 2 weeks of antibiotics fixed it.

yes. I had to heal my gut and kimchi and sauerkraut plus the occasional Kefir are great. I also take from time to time zinc L-carnosine and L-glutamine, great for the gut as well.

It's also a good idea to get tested for H Pilory.

On the other hand, we have seen how perverse incentive amongst experts work too. Academia is rife with fraud (e.g. publishing 500 paper a year), because certain incentives make it possible. I agree expert are important and should be judged by peers, but incentives around budget allocation and prestige should not be attached to performance, especially in science. However I understand it's a complex topic so I probably miss a lot of information, just my 2 c.

This is amazing. Thanks. This also highlights how powerful mind maps / diagrams are when learning cloud products (or other concepts). I used them a lot when studying for my AWS certs and it's amazing how better my mind started understanding interlinked services when presented in a map vs a series of pages, even though I was writing extensive notes. Ofc, YMMV we all learn differently.

I feel like the title is a bit clickbaity. This post is more of a rant against poor management than actual data work per se. That being said it's true that unlike other roles such as developers, artists, copywriters, etc. that still can produce tangible elements of the product under poor leadership, data will be the first victim of poor management and will have a higher probability of not producing anything at all.

Data buy-in within a company is absolutely essential for it to work.

FWIW I've found a lot of value in learning Typescript this year and interacting with the AWS CDK to build infrastructure as code. Upskilling my AWS knowledge also massively paid off, especially networking which I never truly understood before.

In Why We Sleep by Matthew Walker there is a fascinating chapter about how teenagers are biologically programmed to sleep later and wake up later as well. He then explains that basically sending teenagers to school early in the morning is terrible health-wise and prevents optimal brain development.

Anecdata of course but I remember much like you being extremely sleepy at school all day and sleeping a lot on weekends.

For data cleaning I swear by dbt (https://www.getdbt.com/). It's such a powerful tool that you can put in the hand of anyone with SQL knowledge. It allows us to develop clean pipelines, document, and test our data easily. It's also free and the team working there is amazing.

I think you nailed it. Often companies and exec want ML but don't have the basics: robust ETL pipeline, clean data, solid analytics foundation (dashboards, automated reporting, etc.). These appear boring to most but they will be the difference between a useless ML department who can't ship anything to production and a successful one that builds on top of the aforementioned foundations.

In addition I believe it's time we drop the data science term. It's an umbrella of different roles ranging from data engineer to DL researcher. Companies need to identify what they REALLY need and not go for the shiny PhD in ML.

The emergence of analytics engineering is the perfect example of this shift towards creating robust data pipeline first and enabling "data scientists" to do so.

I wrote a blog post about it yesterday, I don't want to post it here and self-promote too much, so check it in my profile if you want to.