I somehow missed that Red Hat abruptly ended Operate First - the #datascience stuff in OpenShift. I had been evaluating it earlier this year in my day job and it looks like I may have definitely dodged a bullet by sticking with upstream Jupyter.
There is no better way to learn a topic than using a real-life example. The Introduction to NFL Analytics with R is a new book by Bradley J.Congelio, focusing on NFL analytics using R, as the name implies. The book covers the following topics:
✅ Introduction to NFL analytics with R
✅ Working with NFL data
✅ Data visualisation applications ❤️
✅ Analysis and modeling of NFL data
Wer macht Dinge mit #DataScience, ist auf dem #CCCamp23 und hätte Lust auf ein kurzes Interview?
Wir planen eine datenleben-Folge mit Kurzinterviews von Data Science Menschen. Was macht ihr? Wie seid ihr da hingekommen? Was begeistert euch an Data Science? So in die Richtung. @naerrin wird mit Mikro und den Fragen auf dem Camp zugegen sein und würde gerne Stimmen einfangen, die dann später zu einer schönen Folge zusammengeschnürt werden sollen. Meldet euch gern via Direktnachricht.
If you're interested in the topic of "Biases and inequalities in machine learning for healthcare", please apply to come and work with me and Prof Jo Knight as part of the CHICAS research group at Lancaster Medical School!
Mona-openai is a new Python package by mona that enables capturing logs to monitor your OpenAI API usage 🚀. That includes cool features such as:
✅ Hallucination alerts
✅ Tokens usage
✅ Behavioral drifts and anomalies
✅ LangChain support
This is a great article by Michael Levinger about the applications of explainable AI for identifying fraud and preventing it. Explainable AI methods help to make black-box models more interpretable and visible. That includes methods such as:
✅ Feature Importance
✅ LIME and SHAP methods
✅ Rule-based Models
✅ Data Visualization
Yesterday a good friend of mine helped me to understand and toy around with Gnu #Guix in a VM as I'm very hesitant to add anything to my daily driver machine. All things considered, I'm >90% convinced.
But here is a question for the friends and the community: What are the advantages of Nix over Guix (apart from number of packages)?
P.s: I'm going to have it on an Arch-based machine to add reproducibility to my projects. It will not handle my OS packages.
Looking for a recommendation(website,Substack, any other material...) where I can improve my SQL knowledge. I am looking for something that I can read(theory) and practice(exercisea). I really enjoy learning python in Substack but until now I have not found something similar for SQL.
📢 Master the Art of List Subsetting in R! 🚀 Or: Lists...again
📝 Lists in R are versatile data structures, capable of holding various elements like vectors, matrices, and even other lists. But what makes them truly magical is the ability to extract specific data efficiently through subsetting. 🎯
🔍 On the #jobhunt! As a Full Stack Developer with experience in #Python, #JavaScript, #React,. I'm looking for new opportunities for #Blockchain, #DataScience, #CAD, #IAQ, and more. I bring versatility to the table with a background in tech writing, community management, and social services.
So is #python the preferred skill set for #datascience nowadays? Is #rstats still an employable skill? I see more an more job ads for data scientists that list python (+ML) as a must but no mention of R...
(1/2) I have been working on a new tutorial during the last few weeks about setting up a dockerized 🐳 Python 🐍 development environment with VScode 💻, and it is finally ready 😎 👇🏼
#CML in action within #Github Desktop: after pushing changes, the action runs and - once the results are ready - the app gives a notification and displays the generated plots