The Curious Engineer

All blogs / AI / ML

Mad (Data) Scientist

matloff.wordpress.com

Musings, useful code etc. on R and data science

AI / MLMathPython

’15’20’25
Posts
123 from 30 Mar 2014 to 14 Nov 2024
Posting
now and then
Kind
personal blog
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2024 7

  1. Package Updates
  2. New qeML Plotting Function
  3. New R Package: Data Science Looks at Discrimination (dsld)
  4. New Paper on Data Privacy
  5. Knowing Something vs. Knowing the Name of Something: Some Points about Causal Analysis
  6. Torch for R Now in the qeML Package
  7. Quantile Regression with Random Forests

2023 6

  1. qeML Example: Nonparametric Quantile Regression
  2. A Comparison of Several qeML Predictive Methods
  3. data.table User Survey
  4. The “Secret Sauce” Used in Many qeML Functions
  5. qeML Example: Issues of Overfitting, Dimension Reduction Etc.
  6. New Package, New Book!

2022 10

  1. New Statistics Tutorial
  2. Just How Good Is ChatGPT in Data Science?
  3. Use of Differential Privacy in the US Census–All for Nothing?
  4. Base-R and Tidyverse Code, Side-by-Side
  5. A New Approach to Fairness in Machine Learning
  6. Valuable Webinar in Parallel Computing in R
  7. Base-R Is Alive and Well
  8. Comments on the New R OOP System, R7
  9. A Major Contribution to Learning R
  10. Greatly Revised Edition of Tidyverse Skeptic

2021 1

  1. Issues in Differential Privacy

2020 5

  1. The Notion of “Double Descent”
  2. Efron Updates breiman’s “two cultures” essay
  3. New Book on Machine Learning
  4. FOCI: a new method for feature selection
  5. “Clearing the Confusion” series

2019 8

  1. R Journal July Issue
  2. New Version of regtools package
  3. Prob/Stat for Data Sci: Math + R + Data
  4. My Free Online Tutorial on R
  5. R vs. Python
  6. r/finance, 1 year later
  7. Free online r course
  8. nice student project

2018 9

  1. R > Python: a Concrete Example
  2. Example of Overfitting
  3. Manifold Visualization: Second Example
  4. Manifold Visualization: Polynomials to the Rescue
  5. What, No Parentheses?
  6. Update on Polynomial Regression in Lieu of Neural Nets
  7. Neural Networks Are Essentially Polynomial Regression
  8. Women in R
  9. Xie Yihui, R Superstar and Mensch

2017 12

  1. Regression Analysis — What You Should’ve Been Taught But Weren’t, and Were Taught But Shouldn’t Have Been
  2. cdparcoord: Parallel Coordinates Plots for Categorical Data
  3. Wrong on an Astronomical Scale
  4. Update on Our ‘revisit’ Package
  5. Understanding Overhead Issues in Parallel Computation
  6. My Presentation at useR! 2017, Etc.
  7. More on R and Reproducible Research
  8. A Partial Remedy to the Reproducibility Problem
  9. Online But In-Class Examinations (with an R Example)
  10. A Python-Like walk() Function for R
  11. Discrete Event Simulation in R (and, Why R Is Different)
  12. Any Forward Progress on p-Values?

2016 19

  1. Threading in R?
  2. Using CART: Implementation Matters
  3. My regtools Package Is Now on CRAN
  4. Manny Parzen Used R!
  5. StatET IDE for R
  6. New Release of partools Package
  7. Bad Coder, Bad Coder!
  8. Latest on the Julia Language (vs. R)
  9. Student-Run Conference in Data Science
  10. Talk on regtools and P-Values
  11. GTC 2016
  12. Even Businessweek Is Talking about P-Values
  13. P-values: the Continuing Saga
  14. Further Comments on the ASA Manifesto
  15. After 150 Years, the ASA Says No to p-values
  16. Quick Intro to NMF (the Method and the R Package)
  17. Innumeracy, Statistics and R
  18. 50% Draft of Forthcoming Book Available
  19. Some Comments on Donoho’s “50 Years of Data Science”

2015 24

  1. The Generalized Method of Moments and the gmm package
  2. The Method of Boosting
  3. OVA vs. AVA in Classification Problems, via regtools
  4. Back to the BLAS Issue
  5. Partools, Recommender Systems and More
  6. A New Method for Statistical Disclosure Limitation, I
  7. Unbalanced Data Is a Problem? No, BALANCED Data Is Worse
  8. More on the Heteroscedasticity Issue
  9. Can You Say “Heteroscedasticity” 3 Times Fast?
  10. New R Software/Methodology for Handling Missing Dat
  11. Exciting userR! 2016 Conference
  12. Partools 1.1.4
  13. partools: a Sensible R Package for Large Data Sets
  14. CACM Highlights R
  15. Heteroscedasticity in Regression — It Matters!
  16. Macros in R
  17. Discovered Two Great Web Sites Today
  18. Update on Snowdoop, a MapReduce Alternative
  19. My New Book and Other Matters
  20. Tutorial on High-Performance Computing in R
  21. GPU Tutorial, with R Interfacing
  22. OpenMP Tutorial, with R Interface
  23. Debugging Parallel Code with dbs()
  24. Snowdoop/partools Package Now on CRAN

2014 22

  1. Snowdoop/partools Update
  2. More Snowdoop Coming
  3. New Package: partools
  4. Snowdoop, Part II
  5. How About a “Snowdoop” Package?
  6. Count Your BLAS-ings
  7. Why Are We Still Teaching t-Tests?
  8. Good for TI, Good for Schools, Bad for Kids, Bad for Stat
  9. Statistics: Losing Ground to CS, Losing Image Among Students
  10. A Matrix Powers Package, and Some General Edifying Material on R
  11. New freqparcoord Example
  12. Code Snippet: Extracting a Subsample from a Large File
  13. A Handy Trick for Remote Graphics
  14. Rth: a Flexible Parallel Computation Package for R
  15. R beats Python! R beats Julia! Anyone else wanna challenge R?
  16. What Can Go Wrong: My Favorite Example
  17. Simpson’s Paradox Is Back
  18. Use of freqparcoord for Regression Diagnostics
  19. More on freqparcoord
  20. Adding Annotation to R Objects
  21. The freqparcoord Package for Multivariate Visualization
  22. New Blog on R, Statistics, Data Science and So On