meztez

25 ms·

1.
by meztez 7mo ago
The best language for AI agents is the one YOU believe is the best.
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by meztez 2y ago
Maybe some, there are also people who cheer for the capacity of humanity to figure out solutions that can benefits humanity. I view the perspective you describe as people externalizing their own insecurity. I do not view it as a critic towa
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by meztez 2y ago
Seems complicated, although this is the best description of depression I've ever read, go outside and start walking.
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by meztez 3y ago
https://docs.posit.co/ , it just makes sense the way everything is organized.
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by meztez 4y ago
A commercial food scale from Kilotech; quicker, more robust, always on, stainless, larger scale area and clear display.
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by meztez 5y ago
For anyone who thinks about doing these, here are a few tips for the advanced CAS exams. - Time is your enemy. - Use memorization techniques, like a memory palace. - Grader are looking for key words, be succinct. - If you do not know, skip.
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by meztez 5y ago
Hated/Loved doing the exams to get my FCAS. It allowed me to explore my mental capacity. It teaches you how to learn fast, how to memorize, how to be quick at solving problems. It has been a while, but after getting involved with the e
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by meztez 5y ago
5 years in. No regret so far. How long before you had regrets?
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by meztez 6y ago
So this is the new bluetooth?
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Spark Microsystems Announces CDN$17.5M Financing Led by Cycle Capital(finance.yahoo.com)
1 points by meztez 6y ago|1 comments
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by meztez 6y ago
Fully agreed. Add `sessionInfo()` output as an appendix to your publication. Should not be too hard to rebuild from that.
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by meztez 6y ago
R has data.table. It is the game changer as I agree base R data.frame do not cut it for performance. tibble will come close once they incorporate more of the data.table performance tricks. https://h2oai.github.io/db-benchmar
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by meztez 6y ago
GPU integration was broken for a long time. Managing VMs / Environments. The absolutely horrible integration with git/Github. Having to rebuild your environment from scratch when your workspace crashed. Imagine starting a notebook
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by meztez 6y ago
It came down to IDE, workflow and data.table. RStudio is an absolute killer solution from the get go. Package management in R is simple and robust. Shiny is the new Excel pivot table on performance enhancing code. Python has more contributo
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by meztez 6y ago
I'm pushing for our actuarial team to transition to more R + Git. After 3 years of preaching, most of the actuaries now use RStudio + git as their primary work tool. It is happening. What we did : 1) Provide documentation on everything
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by meztez 6y ago
RStudio, server and connect are such a treat to interact with compared to anaconda entreprise.
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by meztez 6y ago
A plumber in front of your ML serving function running in a docker container. There, simple, fast enough. We have multiple R containers in production, it is working fine and the data scientist are happy that they can keep working in RStudio
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by meztez 7y ago
Probably because I believe you should wear whatever makes you comfortable within the context of the event you are attending. Women could be wearing suits, and men dresses or skirts, I don't think that matters. And if and it was just do
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by meztez 7y ago
And men told to wear blazer/sport coat, slacks, suit and 'step it up'. I don't see malice in the statement, it is just poorly worded.
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by meztez 7y ago
It is interesting to see this discussion about notebooks while I'm thinking about all the RStudio users who do all their work inside the IDE and are pretty happy. Notebooks seem like such an inferior tool to me. I'm also extremely
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by meztez 7y ago
This comment has to be the most insightful I have ever read. It is true on so many levels and captures perfectly the mentality that some senior decision makers have about AI.
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by meztez 7y ago
Were you using jsonlite? Great library that can parse directly from a URL and transform into data.frame depending on JSON representation. I agree it is not clear from the get go which library should be used when you do something outside of
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by meztez 7y ago
Believe me, I know. The code just becomes unreadable when you put all execution inside the same data step and use hash table to do fast small to big merging. And not to mention debugging that mess when you have a macro layer on top of it. N
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by meztez 7y ago
Debugging is something I could not do as easily in Julia vs debugonce and trace in R. Compiling takes time. But so far we have seen great development. Flux is a truly beautiful ml library. Being a compiled language remove a lot of headache
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by meztez 7y ago
One of the reason we use data.table is that it reduces the depencies when building custom images and its stability has been better than the tidyverse in the past. It might not be the case in the future, but that is how we made our choice in
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by meztez 7y ago
Thanks, so far we just scaled up our vm ram but i might find a use for it.
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by meztez 7y ago
I would highly recommend the use of the package data.table over tibble or the basic data.frame if you are doing any type of modeling in R with larger datasets. Yes R has many data structures but knowing how to use data.table will blow your
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by meztez 7y ago
R is like any other languages, we have a few rest API in production for live prediction. We use rocker docker image with xgboost and plumber, data.table to do pre prediction data wrangling. Hosted on GCP kubernetes, using 0.25 cpu and 250 m
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by meztez 7y ago
I believe people underestimate what can be done in R/RStudio these days because they haven't been exposed to it. R Markdown and its derivative are such great tools. I would also suggest xaringan if you want to present your work on
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by meztez 11y ago
Undeclared sales

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