Lists (5)
Data and interesting projects
Projects or datasources I might want to take inspiration from or use as a source one dayNeat references
Some cool references that I look at from time to time.Stuff I might want to use
Software packages I haven't tried yet, but I kind of want to.Things I like
Software packages and stuff like that. I just think they're neat!To-read
Stuff that I want to read in depth and learn from one dayStars
Data sets and code for the textbook Mathematical Statistics with Resamping and R
[R package]: Datasets from "Applied Logistic Regression" by Hosmer D.W., Lemeshow S. and Sturdivant X.
A collection of datasets well suited to teaching R to beginners
St Gallen University July 2025 Workshop on Causal Panel Methods
🛡🛠 You are being watched. Protect your privacy against global mass surveillance.
A repository to analyze 1.1 million beer advocate reviews
Comparisons between best subset selection and other popular sparse regression estimators
Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.
Markdown-formatted Creative Commons licenses
Markov chain Monte Carlo general, and Hamiltonian Monte Carlo specific, diagnostics for Stan
Prediction of hard drive failure using S.M.A.R.T statistics.
R code and results for the population dynamics analysis of the riverbeds
Scrape beer info and reviews off of beeradvocate
University of Glasgow week-long workshop on causal panel methods
Extensive tutorials for learning how to build deep learning models for causal inference (HTE) using selection on observables in Tensorflow 2 and Pytorch.
Homepage of "Good Description" by Daniel de Kadt & Anna Grzymala-Busse
A template repository with instructions on how to run a targets workflow using the UAz cluster
Data and codes to analyse the reproductive performances of Dijon's tits with regards to the spatial configuration of urban habitats (exclusive data, PubPrivLands project; Martin et al., in prep.)
Material associated with Advanced Quant class 2017
GoogleTest - Google Testing and Mocking Framework
A curated list of free courses from reputable universities that meet the requirements of an undergraduate curriculum in Data Science, excluding general education. With projects, supporting material…
An introductory course on causal inference. Designed for undergraduate students with only a working knowledge of R and multiple regression. Light on maths, heavy on intuition and practical examples.
This course on AI for software development explores the use of AI large language models (ChatGPT, Bard, etc) and their potential benefits and challenges. Hands-on activities show the ways in which …
Spatial Data Science: With Applications in R (source files)