Notes of Practical Machine Learning (Coursera PML)

It has been a long time since I started using R. Recently, I found some old notes, and I prefer to put it in digital archive, this blog post is to achieve the purpose.

DT (data.table) #

data.table cheat sheet

This data.table (DT) instruction is also available on my github, ispiared by
this ref

//TODO #

//TODO: summarize Solve common R problems efficiently with data.table which is must-read. backup
//TODO: summarize High-performance Solution in R
//TODO: check if to summarize Data Analysis in R using data.table
//TODO: Advanced tips and tricks with data.table
//TODO: The official “Getting Started” of DT
//TODO： check tablewrangling.Rmd

CUDA Install

see also:
ways of parallel computing in R

//TODO: study & summarize Map, Gather, Scatter etc.
//TODO: see also the notes for campus’ students assignments.

Coursera Course Notes: _GPU notes.docx
Code: github, or desktop search “gpu assignments”.

Compared with “knn-r-project.Rproj”, “knn_cuda.vcxproj” is at least 6k times faster for almost exactly the same job. (diff: data cleaned; windowSize added.) One reason is the R project was using data.frame instead of tada.table. See here for more R performance info.