1309. Introduction to Data Science: Data Analysis and Prediction Algorithms with R
1310. K-Nearest Neighbor (KNN) Explained
1311. The Ultimate Guide to Deploying a Shiny App on AWS
1312. Controlling for “X”?
1313. The Bias Variance Tradeoff
1314. Double Descent: A Visual Introduction, A Mathematical Explanation
1315. Decision Trees
1316. The Importance of Data Splitting
1317. Bayesian analysis of longitudinal multilevel data using brms and rethinking: Part 1, part 2, part 3, part 4
1318. Deep Neural Nets: 33 years ago and 33 years from now
1319. Just use multilevel models for your pre/post RCT data
1320. R Markdown Tips and Tricks #3: Time-savers & Trouble-shooters
1321. How to create a crisp topographic map in R
1322. How random forests really work
1323. Fast Lane to Learning R
1324. Fun With Parallel Trends
1325. The Existential Threat of Data Quality
1326. A dataset of Roman amphitheaters
1327. How to pick the least wrong colors
1328. Cool Word Clouds in R
1329. Experiments and Surveys on Political Elites
1330. A Very, Very Tiny Grammar of Graphics
1331. Multiple colour scales in choropleth maps with {ggnewscale}
1332. Understanding Contamination Bias
1333. Cluster-robust inference: A guide to empirical practice
1334. GIS and mapping in R: Introduction to the sf package
1335. Common R Mistakes in Data Viz
1336. The Peril of Power when Prioritizing a Point Estimate
1337. Creating flowcharts with {ggplot2}
1338. Numbers Game
1339. The Do’s and Don’ts When Handling Data
1340. Modes, Medians and Means: A Unifying Perspective
1341. Create machine learning models with R and tidymodels
1342. Beautiful tables in R with gtExtras
1343. Plot RGB satellite imagery in true-color with ggplot2 in R
1344. R Screencasts
1345. Creating Confidence Intervals for Machine Learning Classifiers
1346. Tidyverse tips gathered from Dave Robinson’s screencasts
1347. EconHist: a relational database for analyzing the evolution of economic history (1980–2019)
1348. Introducing tidyterra
1349. Generative Modeling by Estimating Gradients of the Data Distribution
1350. Mathematics for Machine Learning
1351. Machine Learning FAQ
1352. Predict Movie Ratings with User-Based Collaborative Filtering
1353. The Biggest Misunderstanding about Behavioural Insights
1354. Is the Pope an alien?
1355. Data for Society
1356. Paper List for Contrastive Learning for Natural Language Processing
1357. Timely Advice – How Long Does Dataviz Take?
1358. Gauges for Data Visualization, The NY Times Election Needle, and Circular Bar Charts
1359. Tableau: Introduction to Tableau, More Tableau, Dashboards in Tableau
1360. Data Science in Context: Foundations, Challenges, Opportunities
1361. Using ggplot2 to create Treatment Timelines with Multiple Variables
1362. Get your data into Wikidata or Wikibase with R: An import workflow derived from a real world project
1363. Supervised Machine Learning for Text Analysis in R
1364. 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
1365. R Workflow
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