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What is “Practical Data Science with R”?

A bit about our upcoming book “Practical Data Science with R”. Nina and I share our current draft of the front matter from the book, which is a description which will help you decide if this is the book for you (we hope that it is). Or this could be the book that helps explain what you do to others.

Continue reading What is “Practical Data Science with R”?

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On Writing Our Book: A Little Philosophy

We recently got this question from a subscriber to our book:

… will you in any way describe what subject areas, backgrounds, courses etc. would help a non data scientist prepare themselves to at least understand at a deeper level why they techniques you will discuss work…and also understand the boundary conditions and limits of the models etc….. ?

[…] I would love to understand what I could review first to better prepare to extract the most from it.

It’s a good question, and it raises an interesting philosophical point. To read our book, it will of course help to know a little bit about statistics and probability, and to be familiar with R and/or with programming in general. But we do plan on introducing the necessary concepts as needed into our discussion, so we don’t consider these subjects to be “pre-requisites” in a strict sense.

Part of our reason for writing this book is to make reading about statistics/probability and machine learning easier. That is, we hope that if you read our book, other reference books and textbooks will make more sense, because we have given you a concrete context for the abstract concepts that the reference books cover.

So, my advice to our subscriber was to keep his references handy as he read our book, rather than trying to brush up on all the “pre-requisite” subjects first.

Of course, everyone learns differently, and we’d like to know what other readers think. What (if anything) would you consider “pre-requisites” to our book? What would you consider good companion references?

If you are subscribed to our book, please join the conversation, or post other comments on the Practical Data Science with R author’s forum. Your input will help us write a better book; we look forward to hearing from you.

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Practical Data Science with R news

We have some great news for “Practical Data Science with R”:

  • We have started an announcement page to point direct readers to the book, book forums, data and the free preview chapter.

Continue reading Practical Data Science with R news

Posted on Categories Administrativia, data science, Exciting Techniques, StatisticsTags , , , , , 7 Comments on Big News! “Practical Data Science with R” MEAP launched!

Big News! “Practical Data Science with R” MEAP launched!

Nina Zumel and I ( John Mount ) have been working very hard on producing an exciting new book called “Practical Data Science with R.” The book has now entered Manning Early Access Program (MEAP) which allows you to subscribe to chapters as they become available and give us feedback before the book goes into print.

Zumel PDSwithR 3

Please subscribe to our book, your support now will help us improve it. Please also forward this offer to your friends and colleagues (and please ask them to also subscribe and forward). Continue reading Big News! “Practical Data Science with R” MEAP launched!

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Spring 2013 Win Vector LLC marketing drive

Dear readers,

I am asking for your help promoting Win Vector LLC and the Win Vector LLC blog ( ). We here at Win Vector LLC try hard to provide quality content and always benefit from more contacts and readers.

If you have any possible leads or can make any introductions to companies that may want some data science consulting I would love to hear from you (email: ).

Also, please subscribe to our data science blog (RSS: and new Twitter account ( ). Better yet please share our blog and Twitter account with anybody you think would be interested (and please ask them to do the same).

Thank you!

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Pragmatic Machine Learning

We are very excited to announce a new Win-Vector LLC blog category tag: Pragmatic Machine Learning. We don’t normally announce blog tags, but we feel this idea identifies an important theme common to a number of our articles and to what we are trying to help others achieve as data scientists. Please look for more news and offerings on this topic going forward. This is the stuff all data scientists need to know.

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Win-Vector starts submitting content to

We have been consistently impressed by and enjoyed the wealth of R wisdom available on the R-bloggers aggregation site.

Therefore Win-Vector LLC is granting the right to reformat and redistribute (with attribution and link) our blog‘s R content in the R-bloggers site and feeds.

We hope to see our R content shared through this network.