– Introduction to Data Science: Data Analysis and Prediction Algorithms with R
– K-Nearest Neighbor (KNN) Explained
– The Ultimate Guide to Deploying a Shiny App on AWS
– Controlling for “X”?
– The Bias Variance Tradeoff
– Double Descent: A Visual Introduction, A Mathematical Explanation
– Decision Trees
– The Importance of Data Splitting
– The Random Forest Algorithm
– Bayesian analysis of longitudinal multilevel data using brms and rethinking: Part 1, part 2, part 3, part 4
– Deep Neural Nets: 33 years ago and 33 years from now
– Just use multilevel models for your pre/post RCT data
– R Markdown Tips and Tricks #3: Time-savers & Trouble-shooters
– How to create a crisp topographic map in R
– How random forests really work
– Fast Lane to Learning R
– Fun With Parallel Trends
– The Existential Threat of Data Quality
– A dataset of Roman amphitheaters
– How to pick the least wrong colors
– Cool Word Clouds in R
– Experiments and Surveys on Political Elites
– A Very, Very Tiny Grammar of Graphics
– Multiple colour scales in choropleth maps with {ggnewscale}
– Understanding Contamination Bias
– Cluster-robust inference: A guide to empirical practice
– GIS and mapping in R: Introduction to the sf package
– Common R Mistakes in Data Viz
– The Peril of Power when Prioritizing a Point Estimate
– Creating flowcharts with {ggplot2}
– Numbers Game
– The Do’s and Don’ts When Handling Data
– Modes, Medians and Means: A Unifying Perspective
– Create machine learning models with R and tidymodels
– Beautiful tables in R with gtExtras
– Plot RGB satellite imagery in true-color with ggplot2 in R
– R Screencasts
– Creating Confidence Intervals for Machine Learning Classifiers
– Tidyverse tips gathered from Dave Robinson’s screencasts
– EconHist: a relational database for analyzing the evolution of economic history (1980–2019)
– Introducing tidyterra
– Generative Modeling by Estimating Gradients of the Data Distribution
– Mathematics for Machine Learning
– Machine Learning FAQ
– Predict Movie Ratings with User-Based Collaborative Filtering
– The Biggest Misunderstanding about Behavioural Insights
– Is the Pope an alien?
– Data for Society
– Paper List for Contrastive Learning for Natural Language Processing
– Timely Advice – How Long Does Dataviz Take?
– Gauges for Data Visualization, The NY Times Election Needle, and Circular Bar Charts
– Tableau: Introduction to Tableau, More Tableau, Dashboards in Tableau
– Data Science in Context: Foundations, Challenges, Opportunities
– Using ggplot2 to create Treatment Timelines with Multiple Variables
– Get your data into Wikidata or Wikibase with R: An import workflow derived from a real world project
– Supervised Machine Learning for Text Analysis in R
– Marginalia: A guide to figuring out what the heck marginal effects, marginal slopes, average marginal effects, marginal effects at the mean, and all these other marginal things are
– R Workflow
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