RStudio Markdowns about R, Math, Stats, and ML
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ECS
EM
GraphicalTools
Kruschke.9.2
PRML
abc
algebra
animation
bayes.packages
bayesnets
benchmarking
biasvariance
bootstrap
bugs
caret
censoring
circular
clustering
combinatorics
copula
decision
discriminant_analysis
distributions
dp
dplyr
factoranalysis
fourier
graphs
ica
inf_theory
interact
langs
manipulate
maps
markov
maxent
missing
naive_bayes
neuralnets
noise
odes
optimization
pca
powerlaw
prob
rbf
regression
spectralclustering
sql
svd
svm
symbolic
tree
ts
variational_inference
web
.gitattributes
.gitignore
Markdowns.Rproj
RClasses.Rmd
RClasses.html
README.md
basisRData.Rmd
basisRData.html
commonFunctions.Rmd
commonFunctions.html
effort.csv
effort.dat
expressions.Rmd
expressions.html
functionalProgramming.Rmd
functionalProgramming.html
index.htm
magrittr.Rmd
magrittr.html
memoization.Rmd
memoization.html
relationalAlgebra.Rmd
relationalAlgebra.html
stringsStuff.Rmd
stringsStuff.html

README.md

My_Markdowns

My R markdowns

R markdowns dealing with lots of concepts from R itself, Bayesian Statistics & Machine Learning

There are lots of code from other people. I hope I included all the references. If not, please tell me, that I will update the markdown.

These pages can also be seen at http://www.di.fc.ul.pt/~jpn/r/

Note: work in progress.