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#datascience

71 posts58 participants0 posts today
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Sarah Lea

Understand RAG at Easter? 🐣 Why not use the time to learn something new — and build your own local PDF chatbot?

Learn how chunking, embeddings and vector search work in practice - with LangChain, FAISS, Ollama and Mistral running entirely on your machine (no API key required).

Perfect for beginners - here's the full guide & GitHub repo 👇

:blobcoffee: step-by-step guide: bit.ly/3EfOHB9
:blobcoffee: GitHub Repo: bit.ly/3EtqYgK

Build your RAG-PDF-Chatbot with LangChain, Python, FAISS, Ollama & Streamlit
#RAG#Langchain#Mistral
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boredsquirrel

Any #DataScience people here?

I have a huge #BeaconDB dataset here, recorded with #NeoStumbler.

I would like to play around with it a bit, display densities of radio devices on a map.

I know #QGis, is it reasonably easy to import a CSV file there, assign the coordinates to some columns etc?

Alternatively I know a bit of #R, but #RStudio is #Electron now, so that could get a hassle XD

Btw, there is a #Fedora #COPR for R-Cran packages, how is the situation on #NixOS?

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Hari_125

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#FullStackAI#AIDevelopment#MachineLearning
Continued thread
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Anthony
We in the US are living in a eugenic modernity, by the way, when the putative head of "Health and Human Services" is making the kinds of statements he makes about autistic people. This is not just an anti-vaccination meme; it's an attempt to subordinate an entire class of people, suggesting they are subhuman for being who they are. This is a eugenic move. One has to wonder whether the "human services" people in HHS imagine themselves providing has to do with "improving the human stock" of the nation, the services not being provided to humans but instead having humans as an output.

Rather than get mired in the thought-terminating arguments around political parties or political factions, though, I think we'd do well to reflect on what sorts of other ways of thinking feed into this one: the measured life; standardized testing; the internet of things (sensors); tracking apps of various kinds; electronic health records; data science as a profession and Big Data generally; predictive modeling; generative AI and other optimization-oriented or productivity-promising technology. All of these function to render life as an object of knowledge in one way or another. All of them trace their origins through eugenics and the patterns of thought that led to it, and all of them threaten to enable and enhance further eugenic thinking. This is not to say these things are always all bad; this is meant to be a reflection on what exactly they're for.

Why read the number of steps your FitBit told you you took today, unless there were some sense in which you want your future self to be better than your present self? It's not an accident that this is called "physical fitness", "fitness" being the Darwinian concept describing which organisms should survive. Why subject children to standardized testing unless there were some belief it made them better students? To what end tends to be left out. Why adopt a technology meant to improve productivity, unless you're of the belief that improvement (optimization) were even possible?

Generally speaking, if one is able to bring oneself to believe that a human being is made better by a data-informed technical intervention, isn't one playing the same game as these anti-autism anti-vaxxers, just with different terminology? If your answer to this provocation is that your data is better than theirs or that you're more aligned with reality than they are--some variation of "the science is on our side"--you've ceded the territory: this is more of the same optimization logic that brought us to this point to begin with. I think we have no choice but to do better than this.

That's my reflection anyway.

#USPol #autism #vaccination #vaccines #antivax #eugenics #BigData #AI #PredictiveModeling #DataScience #science
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