1786. Data Vis Dispatch: April 4, April 11, April 18, April 25
1787. Mastering the Many Models Approach
1788. A Survey of Large Language Models
1789. Balancing Classes in Classification Problems
1790. Plot Prediction Interval in R using ggplot2
1791. Julia’s latency: Past, present and future
1792. A User’s Guide to Statistical Inference and Regression
1793. Why the Cross-Lagged Panel Model Is Almost Never the Right Choice
1794. Deep Learning and Scientific Computing with R torch
1795. Hello Deep Learning
1796. Using fixed and random effects models for panel data in Python
1797. What we learned from creating a custom graphics package in R using ggplot2
1798. Nonresponse rates on open-ended survey questions vary by demographic group, other factors
1799. How we review code at Pew Research Center
1800. Bayesian Regression: Theory & Practice
1801. An Introduction to Data Analysis
1802. Perfect Bar Charts in 150 Seconds
1803. What are people commenting about their loaded packages?
1804. Introducing rtlr – an R Package for RTL Languages
1805. How to Modify Variables the Right Way in R
1806. {surveydown}: An open source, markdown-based survey framework (that doesn’t exist yet)
1807. A data analyst workflow, part 1: SQL & tidyverse
1808. On Efficient Training of Large-Scale Deep Learning Models: A Literature Review
1809. Dependently Typing R Vectors, Arrays, and Matrices
1810. Tidyteam code review principles
1811. The tidymodels is getting a whole lot faster
1812. Making maps with R
1813. Preventing common misconceptions about Bayes Factors
1814. A Course in Machine Learning
1815. Unleash the Power of Functional Programming in R with the purrr Package
1816. Deep Learning Is Better Than Linear Regression
1817. Dev containers with R and Quarto
1818. Styling Tables for Excel with {styledTables}
1819. Deep Learning
1820. Writing performant code with tidy tools
1821. Unlocking the Power of Machine Learning: A Beginner’s Guide to Understanding Algorithms and Models
1822. Charting Our Adventures: How I Created a Personalized Map with R, JavaScript, and more
1823. Differences between the base R and magrittr pipes
1824. Can you have confidence in a confidence interval?
1825. Detecting heart murmurs from time series data in R
1826. What are the differences between R’s new native pipe `|>` and the magrittr pipe `%>%`?
1827. Julia for biologists
1828. The Statistics That Come Out of Nowhere
1829. The Practical Guides for Large Language Models
1830. The Little Book of Deep Learning
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