We overlay the highway network with a massive, geolocated online social network (Twitter 2012), and measure how social ties are impacted by highway segments. We find a strong barrier effect in all 50 considered US cities. See below - the red squares show that this effect is stronger for short distances.
A major release to Ollama - version 0.1.32 is out. The new version includes:
✅ Improvement of the GPU utilization and memory management to increase performance and reduce error rate
✅ Increase performance on Mac by scheduling large models between GPU and CPU
✅ Introduce native AI support in Supabase edge functions
I had previously discussed how to drop those pesky NA records from your data.frame but now, what if you actually want to inspect them? That is what I cover in today's post.
The course Quick & Easy Statistics by Fatai Akemokwe and Afelemo Orilade is on sale on Leanpub! Its suggested price is $44.99; get it for $19.00 with this coupon: https://leanpub.com/sh/z2aczaAD#DataScience
🎉 Full schedule for useR! 2024 (@useR_conf) available now! Incredible line up of tutorials, keynotes, and presentations. Whether you're a seasoned R user or just getting started, this conference is the place to be for exploring the latest in R programming. 📈🖥️
Google released a new repo with a collection of guides and examples for the Gemini API. This includes a set of guides for prompt engineering and examples of the API features 👇🏼
The Learn R Through Examples by Xijin Ge, Jianli Qi, and Rong Fan provides an introduction to data analysis with R. The book covers the core topics of data analysis using different datasets, from simple and clean datasets to messy and big datasets. 🧵👇🏼
Hands-on Data Science: Complete your First Project 🚀
This beginner crash course by Misra Turp provides an introduction to the foundations of data science by solving real-life examples. This includes the different steps of a data science project, from setting the environment to loading and analyzing the data using Python, git, Jupyter notebooks and other tools 👇🏼
This week, PyMC version v5.13.0 was released. PyMC is one of the main #Python 🐍 libraries for 𝐁𝐚𝐲𝐞𝐬𝐢𝐚𝐧 statistics ❤️. It provides a framework for probabilistic programming, enabling users to build #Bayesian models with a simple Python API and fit them using 𝐌𝐚𝐫𝐤𝐨𝐯 𝐂𝐡𝐚𝐢𝐧 𝐌𝐨𝐧𝐭𝐞 𝐂𝐚𝐫𝐥𝐨 (MCMC) methods 🚀.
The new release includes new features, bug fixes 🐞, and documentation improvements 📖. More details on the release notes 📝 👇 #DataScience#machinelearning#statistics
R programmers in The Netherlands, you may be interested in this event with Jenny Bryan about R package development. It is an honour to have her in Utrecht so I hope more people can benefit from this in person opportunity!
(1/2) Models Demystified - A Practical Guide from t-tests to Deep Learning 🚀👇🏼
The Models Demystified is a new book by Michael Clark and Seth Berry that focuses on the mechanizing of core data science algorithms. That includes the following topics:
✅ Linear and logistic regression
✅ Generalized Linear Models
✅ Regularization methods
✅ Model training approaches
✅ Deep learning and neural networks
✅ Causal Modeling