@davidclimentDC @PacktPub The MLwR book is entirely R, but at the office I tend to use R for modeling and analysis, and SQL and Python for data engineering and custom algorithm development.
As someone who buys way too much on Amazon, it brings me a shameful amount of joy to see my book offered as a Prime Day Lightning Deal! ☺️ For the next six hours, it’s available for $21.60… or until supplies run out— they’re going quickly! 🔥
@JuricMislav @ChrisKla47 @PacktPub The book makes no assumptions about prior R experience. It’s designed to get readers up-and-running quickly, even starting from ground zero. That said, a bit of programming background is helpful, but certainly not required.
@Remonicks The link to the PDF with MLwR 3rd edition’s color images should be working now. Thanks for bringing this to my attention. I’m happy you are enjoying the book!
R version 3.6.0 released last week with changes to R’s random number generator. Since MLwR was based on 3.5.2, the book’s code output will not match newer R versions for some functions. There’s an easy fix: simply type RNGversion("3.5.2") before any set.seed() commands.
Note that R version 3.6.0 is expected to release this month with changes to random sampling. This means that the output of some examples will change. Shortly thereafter, I will provide revised code to address this issue. Stay tuned for details!
There are also many subtle changes to explanations, examples, and phrasing based on my experiences teaching from the book. Many frequent questions are preemptively answered. Overall, the book should be much better suited for the classroom environment.
I’m excited to report that the 3rd edition of Machine Learning with R is now available for purchase @PacktPub and other sources! A surprising amount of work went into making this edition clearer, stronger, and easier to use. I hope that the effort shows!
A couple of the examples that used Java-based RWeka now use R implementations of the same algorithms. In particular, the OneR and Cubist packages are now used for rule learning and model trees, respectively.
“Everybody understands that more dollar signs is better” Brett Lantz seems to walk the tightrope between insane complexity and ridiculous simplicity. I love it. #ApraOverDrive2019
A big thanks to #GSERM and the Handelshøyskolen BI school for inviting me to Oslo, Norway to teach Machine Learning with R. It was a busy and challenging two weeks, but I hope that the students got as much from the experience as I did. “Tusen Takk!”
Searching for a last-minute gift for future data spelunkers? For now until the end of the year, Machine Learning with R is 25% off on Amazon. Happy Holidays from @PacktPub! 😀 https://t.co/3iKK5loikQ
Just returned home from a week of teaching ML with R at #GSERM in Medellín, Colombia. I had a great time exploring the city, meeting unbelievably friendly people, and making new friends. Hopefully I can return again soon!
Wrapped up another week of teaching real-world ML methods at #GSERM in beautiful St. Gallen, Switzerland. The days were long, but the week felt short while surrounded by a group of awesome students and interesting people. Already looking forward to next time!
If you missed my Machine Learning courses in Norway and Switzerland, I’m on the schedule for the newest #GSERM in Medellin, Colombia in December 2018. A great opportunity for an audience in the Americas! https://t.co/GKJfGG93DI https://t.co/jqcLp8XJCW
Wrapped up a terrific 1st week teaching Machine Learning with R at #GSERM 2018 in beautiful St. Gallen, Switzerland. Looking forward to a deeper dive next week with the 2nd course in the series, as well as seeing some of my past MLwR alumni! 😀