Science Research Weekly

Episode 28: Everything’s Coming Up Machine Learning

Listen Later

In this episode, I netted new ways to knock neural networks out of the park, let R do my calculus calculations for me, garnered gentle overviews to many   machine learning topics, and made sure my phylogenic trees were publication ready with the R package ‘CancerEvolutionVisualization'.

References:

  • Pathogen.jl: Infectious Disease Transmission Network Modeling with Julia
  • calculus: High-Dimensional Numerical and Symbolic Calculus in R
  • Deep Image Prior for medical image denoising, a study about parameter initialization
  • On Physics-Informed Neural Networks for Quantum Computers
  • Not frequentist enough.
  • ggradar: radar plots with ggplot in R
  • Mastering Debugging in R
  • Understanding leaf node numbers when using rpart and rpart.rules
  • A Gentle Introduction to using Support Vector Machines for Classification
  • Boosting in Machine Learning: A Brief Overview
  • Algorithm Classifications in Machine Learning


    • R-packages:

    • pirouette: Create a Bayesian Posterior from a Phylogeny
    • CancerEvolutionVisualization: Publication Quality Phylogenetic Tree Plots
    • odetector: Outlier Detection Using Partitioning Clustering Algorithms
    • stats4teaching: Simulate Pedagogical Statistical Data
    • camcorder: Record Your Plot History
    • openxlsx2: Read, Write and Edit 'xlsx' Files
      • ...more
      View all episodesView all episodes
      Download on the App Store
      Science Research WeeklyBy Mark R Williamson