rdli

13 ms·

31.
Strategies for Translating Data into Action(amorphousdata.com)
2 points by rdli 3y ago|0 comments
32.
When Metrics Go Awry: Analyzing KPIs Using ML and Shapley Values(amorphousdata.com)
1 points by rdli 3y ago|0 comments
33.
ML and regression analysis to analyze LTV(amorphousdata.com)
1 points by rdli 3y ago|0 comments
34.
by rdli 3y ago
(Author here) One of the things that confused me is that regression models can be predictive, just like time series forecasting — they just do so in a different way. I tried to make this clear in the article (or maybe I’m not understanding
35.
by rdli 3y ago
(Author here). Or a lot of trial & error :).
36.
Time Series Forecasting vs Regression: An informal guide(amorphousdata.com)
175 points by rdli 3y ago|53 comments
37.
by rdli 3y ago
My kids have school-issued devices, and there is a ton of tracking on them. I set up my Pi-Hole on a Raspberry Pi Zero W. I have some brief notes here on my setup: https://www.thelis.org/blog/pi-hole . It works well.
38.
Optimizing SaaS metrics with predictive models(amorphousdata.com)
1 points by rdli 3y ago|0 comments
39.
by rdli 3y ago
Are you using slots ( https://cloud.google.com/bigquery/docs/slots )? If you aren't, I'd highly recommend you switch. My guess is that it would make your costs much more predictable (it did for us). Note t
40.
by rdli 3y ago
I agree that some GCP services are better than others. I’ve never used Pub/Sub or Cloud Run, but have been quite happy with BigQuery and GKE.
41.
Optimizing B2B metrics with predictive models(amorphousdata.com)
1 points by rdli 3y ago|0 comments
42.
Six months of coding with GitHub Copilot(thelis.org)
2 points by rdli 3y ago|0 comments
43.
by rdli 3y ago
I think the #1 thing when you become part of an exec team is that you should be optimizing for the _business_, and not your function. The working assumption is that you will keep your function executing and delivering, but what is really ha
44.
23andMe updates their TOS to force binding arbitration(stackdiary.com)
374 points by rdli 3y ago|244 comments
45.
by rdli 3y ago
At $1M ARR, I think a CFO is overkill (and hideously expensive). In my experience: - $0 - $1M-ish, hire a part-time bookkeeper - $1M - $5M-ish, get a director of finance / controller, who can manage AR/AP, audit, ASC 606, basic fi
46.
by rdli 3y ago
A common strategy is interpolation. The challenge is that forecasting itself is a form of interpolation. So you're forecasting based on forecasted data.
47.
by rdli 3y ago
I tried Prophet via Darts, and all the models in Darts assume a regular time series. Re: "fancier machine learning" -- I've seen different flavors of RNNs & LSTMs have some success in analyzing time series data. I've
48.
by rdli 3y ago
As others have pointed out, Prophet is not a particularly good model for forecasting, and has been superseded by a multitude of other models. If you want to do time series forecasting, I'd recommend using Darts: https://gith
49.
Using Deep Learning to analyze data(thelis.org)
2 points by rdli 3y ago|0 comments
50.
by rdli 3y ago
Another parallel that I see is “cloud”. Salesforce was one of the first (if not the first) real successful cloud companies. But it took a really long time (and it still is going on) for cloud-first to be the default in enterprises. And alon
51.
by rdli 3y ago
Temporal Fusion Transformer: see https://arxiv.org/abs/1912.09363 .
52.
Why lasers could help make the electric grid greener(npr.org)
6 points by rdli 3y ago|0 comments
53.
by rdli 3y ago
I found it helpful for prototyping and learning some basics, but I quickly found the abstractions were not useful and had to implement my own.
54.
by rdli 3y ago
https://www.thelis.org/blog Mostly notes to myself, and I’ve got a half-baked post on LLMs that I’ve been working on (as that’s been my area of recent interest).
55.
by rdli 3y ago
Location: Boston, MA Remote: Yes, or in Boston Willing to relocate: No Technologies: Kubernetes, Envoy, LLMs, service mesh, Hugging Face, Python, SQL, BigQuery, DBT, LangChain, Docker Résumé/CV: https://www.linkedin.com&#x2F
56.
by rdli 3y ago
There's definite leaching of plastic compounds into food, which gets exacerbated when heated. My concern is the number of unknown unknowns. BPA became a big part of the consciousness a few years ago, and now it's PFAs, but what el
57.
by rdli 3y ago
I don't think Scanpan is PFA free: https://www.scanpan.com/chemical-components .
58.
by rdli 3y ago
We've worked to reduce plastics & chemicals in our house. Some things we do: * We use silk dental floss (we use Radius) * We use glass storage containers instead of Tupperware * For cooking, we use All-Clad. * If a recipe calls for
59.
by rdli 3y ago
Location: Boston, MA Remote: Yes, or in Boston Willing to relocate: No Technologies: Kubernetes, Envoy, LLMs, service mesh, Hugging Face, Python, SQL, BigQuery, DBT, LangChain, Docker Résumé/CV: https://www.linkedin.
60.
by rdli 3y ago
I was an early member of the CNCF community (circa 2016), and at the time I thought "wow things are moving quickly." Lots of different tech was being introduced to solve similar problems -- I distinctly remember multiple ways of t

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