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Freelancer: HD Edition is a mod that aims to improve every aspect of the game Freelancer (2003) while keeping the look and feel as close to vanilla as possible.
This is a repo for all the tutorials put out by H2O.ai. This includes learning paths for Driverless AI, H2O-3, Sparkling Water and more...
Collection of useful machine learning codes and snippets (originally intended for my personal use)
STAT 451: Intro to Machine Learning @ UW-Madison (Fall 2020)
Fit interpretable models. Explain blackbox machine learning.
Code and Resources for "Feature Engineering and Selection: A Practical Approach for Predictive Models" by Kuhn and Johnson
Additional resources for the UC BANA 7025 Data Wrangling course
A demo of an end-to-end machine learning pipeline, using Posit Connect
Source and slides for "Why you should be using tidymodels" at UW-Madison
tidymodels tutorial for the Statistical Society of Australia (SSA) statistical computing and visualisation tutorials
EPFL Machine Learning Course, Fall 2024
R Scripts from the 2018 International Summer School in Lausanne
Material for the 2-day block course "Deep Learning with Actuarial Applications in R"
Code for the Actuarial Data Science Tutorials published at https://actuarialdatascience.org.
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
Main repository for R programming courses @ University of Cincinnati, courses and tutorials that focus on data wrangling, exploration, visualization, and analysis with R.
Website and materials for tidymodels workshops
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
Additional resources for the UC BANA 4080 Data Mining course
Intermediate R training material delivered in a 2 day format
H2O.ai Machine Learning Interpretability Resources
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
A curated list of awesome responsible machine learning resources.
A topic-centric list of HQ open datasets.
A dump of all the data science materials (mostly pdf's) that I have accumulated over the years
Notes and exercise attempts for "An Introduction to Statistical Learning"
Code and resources for the 2nd edition of "Hands-on Machine Learning with R: An applied book covering the fundamentals of machine learning with R" by Boehmke & Greenwell