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
Recent @DSLC club meetings:
Health Metrics and the Spread of Infectious Diseases: Essential R Packages for Machine Learning https://youtu.be/Tk11cfXti_Y #RStats
Shiny Club https://youtu.be/IN-mlShrNVA #RStats #RShiny
Generative AI Handbook: Finetuning Methods for LLMs https://youtu.be/R8ECITSFT1Q #PyData #GenAI #AI #DeepLearning
Visit https://dslc.video for hours of new #DataScience videos every week!
A Simple Path to Python Success http://leanpub.com/set/leanpub/asimplepathtopythonsuccess is the featured Track of online courses on the Leanpub homepage! https://leanpub.com #ComputerProgramming #Devops #python #data #datascience
Atlassian is hiring a Manager - Data Science
Location: 
San Francisco, California, United States
Salary: $167100 - $268400
#DataScience #DataScientist #tech #JobSearch #GetFediHired #HashyJobs #US #Atlassian
https://datasciencejobs.com/jobs/manager-data-science-atlassian-united-states-15/
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
https://www.theleftshift.com/openai-admits-newer-models-hallucinate-even-more/
It's For The Best
https://youtu.be/dfvsmP9EMSY?si=jiS8J70EtyddGSIY
"They'll love it."—old friend of mine whose name starts with a J in which I am not sure he wants to be mentioned.
In the context of software development, I usually reject the idea that we should run experiments for every single "change".
If the expected impact is significantly lower than your minimum detectable effect, you should probably not waste resources running the experiment.
However, sometimes I get the question "what if I have no idea of what the impact is going to be?"
I'll admit I don't have an answer to that. Not a polite one at least. #datascience
"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."
Can AI Be Trained on Data Generated by Other AI? Exploring the Potential and Pitfalls of Synthetic Training Data
AI-generated training data is revolutionizing AI model training! Synthetic data simulates real-world scenarios, offering a more efficient approach. Companies like Anthropic are already using it. Learn more about this exciting new frontier! #SyntheticData #AIGeneration #AItraining #DataScience #MachineLearning #FutureofAI
https://tech-champion.com/data-science/can-ai-be-trained-...
Graph learning has evolved significantly. Early work in graph analysis was all about uncovering hidden patterns and relationships. Discover the journey here: https://ift.tt/9Rdnfbq #GraphLearning #DataScience #Evolution #Analytics #byAI
Commonwealth Bank is hiring a Senior Associate Data Scientist
Location: 
Bangalore, India
#DataScience #DataScientist #tech #JobSearch #GetFediHired #HashyJobs #
https://datasciencejobs.com/jobs/senior-associate-data-scientist-commonwealth-bank-india-13/
Longitudinal Data Analysis Using R by Alexandru Cernat is on sale on Leanpub! Its suggested price is $65.00; get it for $45.50 with this coupon: https://leanpub.com/sh/lLKThwnA #R #Textbooks #DataScience #Software
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 
step-by-step guide: https://bit.ly/3EfOHB9 GitHub Repo: https://bit.ly/3EtqYgK
Cantina Labs is hiring a Machine Learning Infrastructure Manager
Location: San Francisco, California, United States
Salary: $200000 - $250000
#DataScience #DataScientist #tech #JobSearch #GetFediHired #HashyJobs #US
https://datasciencejobs.com/jobs/ml-infrastructure-manager-cantina-labs-united-states-2/
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?
Given:
```
import numpy as np
arr3d = np.array([[[1,2,3], [4,5,6]],[[7,8,9], [10,11,12]]])
```
What is the result:
```
old = arr3d[0].copy()
arr3d[0] = 42
print(arr3d,'\n')
arr3d[0] = old
foo = arr3d[1, 0]
bar = arr3d[1]
foo == bar[0]
```
Tags: #python #datascience #ai #tech #linux #opensource
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OpenDataCity stellt mit #redata14 strukturierte Daten zur #republica bereit – u.a. zu Talks, Personen & Hashtags. Ideal für #DataViz & #DH-Projekte!
https://github.com/opendatacity/re-data/tree/master/data/rp14
#OpenData #DigitalHumanities #DataScience
