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#datascience

43 posts38 participants5 posts today
Public
rOpenSci

Evento: Desarrollando Paquetes de R con ayuda de rOpenSci

Junto con R-Ladies Santa Rosa y R-Ladies Rcia-Ctes el 23 de abril a las 17:00 UTC-3

📦 Introducción al desarrollo de paquetes y al Programa de Campeones en español y con foco en América Latina.

+info + link to join: ropensci.org/events/rladies-ch

ropensci.orgDesarrollando Paquetes de R con ayuda de rOpenSciHablaremos sobre herramientas clave para desarrollar paquetes de R y cómo participar en el Programa de Campeones de rOpenSci.
#RStats#DataScience#CienciaDeDatos
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Henrik Schönemann

Friends don't let friends use iris, those flowers are not innocuous:
"Many people using iris will be unaware that it was first published in work by R A Fisher, a eugenicist with vile and harmful views on race. In fact, the iris dataset was originally published in the Annals of Eugenics. It is clear to me that knowingly using work that was itself used in pursuit of racist ideals is totally unacceptable."
meganstodel.com/posts/no-to-ir
#datascience #data

Megan Stodel · Stop using irisThe iris dataset is very widely used in the data science community, whether as a training aid, a tool for trying out new skills, or just a well-known set of numbers that can be used as background while demonstrating something in a blog.
Public
Eric R. Scott

I got some unfortunate news earlier this month: #UniversityOfArizona has decided to defund the group I work for, @cct-datascience.bsky.social, amidst their continuing budget crisis.

datascience.cct.arizona.edu/ne

It super sucks and means I'll likely have to drop down to 50% in May and I'll be looking for new, better supported, #rseng or #datascience positions, ideally still working with biologists in #rstats in some capacity. Remote or in #Tucson.

Let me know if you know of anything!

Data Science Team · Data Science Team seeking new projects after losing funding
Public
datatofu

I have previously mentioned software standards in passing.

The top-level standard is ISO/IEC Std 12207, Information Technology—Software Life Cycle Processes, which is the international standard that defines a life-cycle framework for developing and managing (ALL) software projects.

This standard was adopted in the United States as IEEE/EIA Std 12207, Information Technology—Software Life Cycle Processes.

Obviously, there are more

Tags: #ai #python #datascience #tech #linux #opensource

Public
datatofu

The common sense of high-quality programming

•Constructing quality classes and routines is an iterative process.

•Writing good pseudocode calls for using understandable English, avoiding language specific features, and writing at the level of intent

•The PPP is a useful tool for detailed design and makes coding easy

•Iterate through multiple approaches

•Check your work at each step

Tags: #ai #python #rstats #tech #linux #datascience

Public
Jürgen

No robust solution in sight. #LLM progress is stagnant?

“According to #OpenAI’s internal benchmarks, their newer models– o3 and o4 mini– hallucinate more often than older reasoning models like o1, o1-mini, and o3-mini, as well as traditional models such as GPT-4”

#AI #tech #technology #datascience

theleftshift.com/openai-admits

The Left Shift · OpenAI Admits Newer Models Hallucinate Even MoreIn a technical report, the company said “more research is needed” to explain why hallucinations increase as reasoning capabilities scale
Replied in thread
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Valeriy M., PhD, MBA, CQF

Thank you to everyone already reading, sharing, and applying these ideas. Let’s keep pushing the boundaries of what machine learning can trust.

#MachineLearning #UncertaintyQuantification #ConformalPrediction #AI #DataScience #ML #PolitecnicoDiMilano #3xAuthor

valeman.gumroad.com/l/advanced

GumroadAdvanced Conformal Prediction: Reliable Uncertainty Quantification for Real-World Machine Learning (preorder - release in 2025)🚀 Advanced Conformal Prediction: Reliable Uncertainty Quantification for Real-World Machine Learning 🚀 (Early Access)Are you ready to take your machine learning models to the next level? Move beyond basic predictions and master advanced techniques for quantifying and managing uncertainty with confidence.In "Advanced Conformal Prediction," you'll dive deep into sophisticated methods designed to enhance reliability and decision-making in real-world AI applications. This comprehensive guide equips you with practical skills and cutting-edge tools, empowering you to confidently deploy machine learning solutions in high-stakes environments.Whether you're a data scientist, engineer, researcher, or practitioner, this book will become your essential resource for ensuring the trustworthiness of your AI models.📖 What's Inside: Advanced methods for uncertainty quantification Practical insights for real-world AI deployment Techniques for improving model reliability Join the journey and transform your approach to AI uncertainty today!🌟 Perfect for: Data Scientists and ML Engineers AI Researchers Professionals deploying ML in critical industries Secure your copy now and revolutionize how you manage uncertainty in machine learning!
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Miguel Afonso Caetano

"This paper advances the critical analysis of machine learning by placing it in direct relation with actuarial science as a way to further draw out their shared epistemic politics. The social studies of machine learning—along with work focused on other broad forms of algorithmic assessment, prediction, and scoring—tends to emphasize features of these systems that are decidedly actuarial in nature, and even deeply actuarial in origin. Yet, those technologies are almost never framed as actuarial and then fleshed out in that context or with that connection. Through discussions of the production of ground truth and politics of risk governance, I zero in on the bedrock relations of power-value-knowledge that are fundamental to, and constructed by, these technosciences and their regimes of authority and veracity in society. Analyzing both machine learning and actuarial science in the same frame gives us a unique vantage for understanding and grounding these technologies of governance. I conclude this theoretical analysis by arguing that contrary to their careful public performances of mechanical objectivity these technosciences are postmodern in their practices and politics."

journals.sagepub.com/doi/10.11

#DataScience#STS#Insurance
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