Why Every Media Team Needs an Analytics Agent
From dashboards to decisions — AI is now the analyst. Explore how analytics agents are transforming media teams by providing instant insights and automated analysis. [Read more...]
Why and How to Calculate Retirement Ruin Probability?
What will you learn from this article?
Jorge Guinle—the famous Brazilian playboy—died on Friday the fifth of March 2004 in Rio de Janeiro. Jorge was born to one of the wealthiest families in Brazil, and he spent a large part of his life ...
Exploring `RSQLite` With `DBI`: A Note To Myself
I messed around with DBI and RSQLite and learned it’s actually pretty simple to use in R - just connect, write tables, and use SQL queries without all the complicated server stuff. Thanks to Alec Wong for suggesting this!
Motivation
After our last
blog, my friend Alec Wong suggested ...
Repost: R 4.5.0 and Bioconductor 3.21
Reposted from the original at https://blog.stephenturner.us/p/r-450-bioconductor-321.Faster package installation, import only the functions you want with use(), built-in Palmer penguins data, grep values shortcut, and lots of new bioinformatics pa...
Welcome, Ashley Tarasiewicz
Hello pharmaverse community!
I’m thrilled to announce that Ashley Tarasiewicz will be taking over the Atorus seat from me on the Pharmaverse council.
Ashley has been a contributor to the pharmaverse since the early days of its inception, contr... [Read more...]
Welcome, Ashley Tarasiewicz
Hello pharmaverse community!
I’m thrilled to announce that Ashley Tarasiewicz will be taking over the Atorus seat from me on the Pharmaverse council.
Ashley has been a contributor to the pharmaverse since the early days of its inception, contr... [Read more...]
Running R on Windows on ARM on GitHub Actions
Introduction
GitHub has recently announced that Windows ARM64 runners are
now available under the windows-11-arm label.
I help maintain an R package,
TwoSampleMR, which has quite alot of users. The package is not on CRAN because several of its depend... [Read more...]
Announcing the Jumping Rivers Dashboard Gallery
At Jumping Rivers we love data dashboards and are delighted to announce the release of a
gallery to showcase our application-development
skills.
Tools like
Shiny,
Dash,
Streamlit and
Observable have simplified the process of making interactive, v...
Assessing rating scale dimensionality through bifactor model-based indices in R workshop
Join our workshop on Assessing rating scale dimensionality through bifactor model-based indices in R, which is a part of our workshops for Ukraine series! Here’s some more info: Title: Assessing rating scale dimensionality through bifactor model-based indices in R Date: Thursday, May 15th, 18:00 – 20:00 CET (Rome, Berlin, Paris timezone) Speaker: ... [Read more...]
K-Means Clustering Analysis of Apple, Microsoft, and Nvidia
The exemption of key electronic components from tariffs is likely to positively impact Apple more, which manufactures approximately 90% of its iPhones in China, compared to other tech giants like Microsoft and Nvidia. Furthermore, the k-means clustering chart shows that Apple has diverged year to date, specifically after the April 2 tariffs. ... [Read more...]
Sport data from Runalyze
Runners – CC-BY by ~jar{}
I already explored how to get your activities from Strava. Maybe you use Runalyze instead? In that case you can do some web scraping to export your data.
library(httr)
library(rvest)
library(glue)
library(read...
Choroplethr v4.0.0 is now on CRAN
choroplethr version 4.0.0 is now on CRAN. You can install it like this: With this version, I have transferred the maintenance of choroplethr to Zhaochen He, an economics professor at Christopher Newport University. Zhao addressed the issues that led to choroplethr being archived from CRAN in February. Please join me in ...
Benchmarking
Goal
We will go beyond resampling single learners. We will learn how to compare a large number of different models using benchmarking. In this exercise, we will not show you how to tune a learner. Instead, we will compare identical learners with...
Train Predict Evaluate Basics
Goal
Our goal for this exercise sheet is to learn the basics of mlr3 for supervised learning by training a first simple model on training data and by evaluating its performance on hold-out/test data.
German Credit Dataset
The German credit dat... [Read more...]
Resampling Solution
Goal
You will learn how to estimate the model performance with mlr3 using resampling techniques such as 5-fold cross-validation. Additionally, you will compare k-NN model against a logistic regression model.
German Credit Data
We work with the...
Tree Methods
Goal
The goal for this exercise is to familiarize yourself with two very important machine learning methods, the decision tree and random forest. After this exercise, you should be able to train these models and extract important information to ... [Read more...]
Train Predict Evaluate Basics Solution
Goal
Our goal for this exercise sheet is to learn the basics of mlr3 for supervised learning by training a first simple model on training data and by evaluating its performance on hold-out/test data.
German Credit Dataset
The German credit dat... [Read more...]
Benchmarking
Goal
We will go beyond resampling single learners. We will learn how to compare a large number of different models using benchmarking. In this exercise, we will not show you how to tune a learner. Instead, we will compare identical learners with...
Tree Methods
Goal
The goal for this exercise is to familiarize yourself with two very important machine learning methods, the decision tree and random forest. After this exercise, you should be able to train these models and extract important information to ...
Resampling
Goal
You will learn how to estimate the model performance with mlr3 using resampling techniques such as 5-fold cross-validation. Additionally, you will compare k-NN model against a logistic regression model.
German Credit Data
We work with the...
Copyright © 2026 | MH Corporate basic by MH Themes