[This article was first published on Mad (Data) Scientist, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
Sorry I haven’t been very active on this blog lately, but now that I have more time, that will change. I’ve got myriad things to say.
To begin with, then, I’ll announce a major new R package, and my new book.
qeML package (“quick and easy machine learning”)
Featured aspects:
- Now on CRAN, https://cran.r-project.org/package=qeML.
- See GitHub README for intro, https://github.com/matloff/qeML.
- Extremely simple, “one liner” user interface.
- Ideal for teaching: very simple interface, lots of included datasets, included ML tutorials.
- Lots for the advanced MLer too: special ML methods, advanced graphics, etc.
- Lots of related “nuts and bolts” infrastructure functions, e.g. involving R factor conversion.
The Art of Machine Learning, N. Matloff, NSP, 2023
- For those without prior ML background. (Experienced MLers may learn a thing or two as well.)
- Anti-“cookbook”: Aims to empower readers to actually use ML in real, non-“sanitized” applications.
- Really gets into the How? and Why? (and for that matter, the Why Not?).
- Uses the qeML package.
- See my writeup on the philosophy of the book, https://github.com/matloff/ArtOfML.
To leave a comment for the author, please follow the link and comment on their blog: Mad (Data) Scientist.
R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.