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awesome-quarto

A curated list of Quarto talks, tools, examples & articles! Contributions welcome!

aws-mlu-explain

Visual, Interactive Articles About Machine Learning: https://mlu-explain.github.io/

bayes

Material for teaching Bayesian data analysis

bda_course_aalto

Bayesian Data Analysis course at Aalto

book

c-cpp-notes

Lecture notes and example code for teaching C & C++

chatgpt-data-science-prompts

A repository of 60 useful data science prompts for ChatGPT

cmdstanr

CmdStanR: the R interface to CmdStan

correlation-measures

Raw files for a summary of various measures of dependency.

covid-19-data

Data on COVID-19 (coronavirus) cases, deaths, hospitalizations, tests • All countries • Updated daily by Our World in Data

covid-19-excess-deaths-tracker

Source code and data for The Economist's covid-19 excess deaths tracker

covid-19-it

Statistical Modelling of COVID-19 Outbreak in Italy

covid19-r

Collection of analyses, packages, visualisations of COVID-19 data in R

covindex

data-analysis-with-r

Using gglot2, tidyr, dplyr, ggmap, choroplethr, shiny, logistic regression, clustering models and more

data-science-in-tidyverse

Materials for Data Science in the Tidyverse, a two-day workshop @ rstudio:conf(2019)

datasciencecoursera

Coursera DataScience

datavisguide

Introductory guide to the art and science of data visualisation. Insights, advice, and examples (with code) to make data outputs more readable, accessible, and impactful.

distribution_diagrams

R-script for generating canonical diagrams of distributions to be used to describe Bayesian hierarchical models.

fiveminutestats

A repo of short "vignettes" illustrating statistical concepts

fraud-autoencoder-example

Repository with files used for the blog post "Predicting Fraud with Autoencoders and Keras"

ga

An R package for optimization using genetic algorithms

gmm_entropy_anomaly_detection

gsir-te

Getting Started in R -- Tinyverse Edition

h2o-tutorials

Tutorials and training material for the H2O Machine Learning Platform

handson-ml2

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

hidden-markov-random-fields

Implementation of HMRF in Python

icons

R package to easily insert web icons to RMarkdown

intro-gam-webinar-2020

labs

Scripts for HarvardX courses: PH525x