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Listen "Episode 39: Last Stat Before Christmas"
Episode Synopsis
In this episode, I pondered the problem of false positives in publications, rotated around the JuliaHub, machinated over machine learning projects, and put R package ‘drawCell’ to the test.
References:
Are most published research findings false in a continuous universe?
Principal component analysis
A no-free-lunch theorem for multitask learning
JuliaHub
Signal-to-noise ratio and statistical tests
Large Enough Sample Condition
Top 11 Interesting Machine Learning Project Ideas For 2023
Code longevity of the R programming language
{drawCell} – R package and Shiny app for drawing cell structures
R-packages:
colorRamp2: Generate Color Mapping Functions
rworkflows: Test, Document, Containerise, and Deploy R Packages
MetChem: Chemical Structural Similarity Analysis
panelsummary: Create Publication-Ready Regression Tables with Panels
arf: Adversarial Random Forests
References:
Are most published research findings false in a continuous universe?
Principal component analysis
A no-free-lunch theorem for multitask learning
JuliaHub
Signal-to-noise ratio and statistical tests
Large Enough Sample Condition
Top 11 Interesting Machine Learning Project Ideas For 2023
Code longevity of the R programming language
{drawCell} – R package and Shiny app for drawing cell structures
R-packages:
colorRamp2: Generate Color Mapping Functions
rworkflows: Test, Document, Containerise, and Deploy R Packages
MetChem: Chemical Structural Similarity Analysis
panelsummary: Create Publication-Ready Regression Tables with Panels
arf: Adversarial Random Forests
In God we trust